AI ethics on Monday, 20 July 2026

Young, old, midlife – whatever your age, gender or sector, the unemployment crisis is hitting us all. The only way through it is together The personal experience of long-term unemployment is one people rarely share, for completely understandable reasons. There’s a bit of superstition that saying it out loud will bed it in, and there’s always one person in 100 who will choose to explain away the misfortune as your own personal failing. Even if they’re clearly in the grip of superstitions of their

World leaders are marching us toward an uncertain era of new warfare — fast.

The next time you apply for a job, AI may screen your résumé before any human sees it. But there’s good reason to question whether AI will judge you fairly. Researchers already know that LLMs pick up human biases from their training data. New research suggests that LLMs can also develop their own biases from…

Company aims to develop AI software that cuts research times and use of rare metals in chipmakers’ supply chains Business live – latest updates Amazon’s founder, Jeff Bezos, and the UK government have invested in a £2bn British artificial intelligence startup that is aiming to become the “search engine for rare materials” that accelerates the next wave of technological breakthroughs. The Cambridge-based CuspAI has raised $450m (£330m) in funding from investors including Bezos and the government’

Sony Music Entertainment has filed another lawsuit against Udio, accusing the AI music generator of infringing the copyright of more than 30,000 of its songs, ranging from Elvis Presley's Hound Dog to Beyoncé's Say My Name, and Harry Styles' As It Was. The lawsuit, filed in a New York court on Monday, claims that this […]

Universities’ crackdown on the use of AI misses the point. They should instead teach it as a vital productivity tool, undepinned by ethics.

Increased power costs add to challenges facing tech giant’s AI ambition amid high spending and mounting debt

As hospitals increasingly use AI to improve patient care, the same technology is being used by hackers and nation-states to launch faster, more sophisticated attacks. Karen Habercoss, chief information security and privacy officer at the University of Chicago Medicine, explained how her health system is building a governance structure to manage that risk. The post The Same AI That Helps Patients Is Being Used to Attack Them, Hospital Exec Says appeared first on MedCity News .

Biglaw is widening its net. The post T14 Degrees Aren’t All That Anymore… appeared first on Above the Law .

Chinese robotics companies lack both sufficient data and a good “brain” to improve the interaction of their products with the physical world, according to industry insiders at the World Artificial Intelligence Conference (WAIC), which concluded on Monday in Shanghai. The most critical challenge for the embodied AI industry was to “link hardware, data, models and real-world scenarios into a closed-loop iterative system”, said Wang Xiaogang, co-founder of SenseTime and chairman of its robotics...

Scaling AI, Agentic AI and Data Sovereignty & Compliance.

Iran's interior minister traveled to Pakistan, a key mediator in the conflict, for talks.

“The threat environment has changed" and the lines between physical and digital attacks have blurred, said one security expert involved in FIFA World Cup Planning.

Your tour of all things related to lawyer and judicial ethics, with University of Houston law professor Renee Knake Jefferson. The post Legal Ethics Roundup: SCOTUS Justices Testify About Enforceable Ethics, 20 AGs Want Clark Discipline Challenge Dismissed, Law Democratized On LawNext & More appeared first on Above the Law .

Defense Secretary Pete Hegseth is requiring service members to screen for low testosterone levels. Ironically, the military lifestyle itself is more likely to lower T levels.

It's a step toward making alternative energy accessible on a smaller, renter-friendly scale.

Barely three days after disclosure, attackers are widely chaining together CVE-2026-60137 and CVE-2026-63030 to lob exploit attempts against one of the largest attack surfaces on the Internet.

Lawyers create value by understanding people. The post Angela Madathil Is Right: The Best In-House Lawyers Aren’t Compliance Police. They’re Translators. appeared first on Above the Law .

Clarence Thomas mused that the Commerce Clause may not support most federal law and the Fifth Circuit fell all over themselves to take it up. The post To Help Heroin Trafficker Keep His Gun, Fifth Circuit Considers ‘What If We Got Rid Of All Federal Laws?’ appeared first on Above the Law .

Too tricky? Resign. The post The Ways That Congress Should Regulate Itself appeared first on Above the Law .

Displayed in a truck mounted configuration at the show, the new MBDA weapon is an upgrade to the company’s ground-launched, Advanced Short Range Air-to-Air Missile (ASRAAM) and can also be integrated on unmanned ground vehicles or unmanned surface vessels.

To a private equity firm.

Ivanti CSO Daniel Spicer says frontier models have shown surprising effectiveness in early stages; but cost and human-in-the-loop viability remain open questions.

Arvind Raman, the director of National Institute of Standards and Technology, will serve as acting director of CAISI, according to a spokesperson

Flight logs show the FIFA President utilized a private jet gifted by World Cup sponsor Qatar Airways to travel to 21 different airports throughout the tournament.

The meeting came ahead of a markup planned for next week on AI policy and kids online safety measures.

Archer and its eVTOL peers are racing for FAA certification to start flying their air taxis commercially.

And he's working as a Biglaw summer associate at the same time. Wow! The post Harvard Law Student Has Already Won Nearly $350K On Jeopardy! appeared first on Above the Law .

Kai-Fu Lee’s 01.ai is raising a pre-IPO round ahead of a planned Hong Kong listing in 2027, the former Google China chief told Bloomberg at the World AI Conference in Shanghai. The company is unwinding its offshore holding structure, the same prerequisite that Moonshot dismantled in May to clear its own path to a Hong […] This story continues at The Next Web

Eightcap uses AI to scale compliance across global markets.

Journey Beyond finds safer path to customer AI with agentic agents.

The agency questions USAC’s processes, expenses, governance structure and long-term role as the Universal Service Fund’s administrator.

Neo emerged from stealth on Monday with $100 million in funding from Andreessen Horowitz and Bessemer Venture Partners, with Craft Ventures and Merlin Ventures also participating. The company, founded by former SentinelOne, Wiz, and Palo Alto Networks executives, is building what it calls a real-time control layer for agentic software in the enterprise. The problem […] This story continues at The Next Web

Smokey and the Bandit 4's extended Supreme Court oral argument scene is going to be LIT! The post SCOTUS To Decide If Cops Can Steal 82-Year-Old’s Plane Over Passenger’s Bud Lights appeared first on Above the Law .

Job pressures have increased as companies run headlong into AI adoption, causing 26% of top security executives to consider leaving their position.

Netflix has teamed up with a company called SignUp Media to offer ASL interpretations on a bunch of kids shows and movies.

How defense agencies can build a skills-based workforce without rebuilding from scratch. The post From job descriptions to skills intelligence appeared first on DefenseScoop .

This is the case that keeps on giving. The post DOJ Wants Susman Godfrey Kicked Off The ABA’s Case Because DOJ Subpoenaed Susman Godfrey appeared first on Above the Law .

"The TFF Trap" uses fileless techniques and loaders with low detection rates to deploy various RATs and stealers, including Agent Tesla, Remcos, XWorm, and Best Private Logger.

How defense agencies can build a skills-based workforce without rebuilding from scratch. The post From job descriptions to skills intelligence appeared first on FedScoop .

Nearly every child in Hawaiʻi lives in a community that lacks adequate licensed childcare, with access rates falling far behind the national average, according to recent reports from the Center for American Progress. Challenges finding affordable childcare have also worsened for some families this year as they face delays with receiving state subsidies reducing the […]

Dr. Chris Fall, the director of the Commerce Department's Center for AI Standards and Innovation (CAISI) is resigning after just three months in the role. The exit of Fall, who was appointed to head the AI safety organization in April, comes amid a fluctuation in the Trump administration's AI policy. Staff at CAISI are directly...

A new, gonzo style of fraud could be an existential threat to prediction markets.

Baker McKenzie's global chair says AI demands a new way of thinking about legal fees. The post Biglaw May Want To Break Up With The Billable Hour Thanks To AI appeared first on Above the Law .

Over the past nine months, Amazon, Microsoft, and Google have each introduced or renamed an enterprise agent platform. And all The post Amazon, Microsoft, and Google are converging on the same enterprise agent architecture appeared first on The New Stack .

Over the past nine months, Amazon, Microsoft, and Google have each introduced or renamed an enterprise agent platform. And all The post Amazon, Microsoft, and Google are converging on the same enterprise agent architecture appeared first on The New Stack .

Primary “targets of interest” that the service might want to zap include aerial and maritime drones. The post Coast Guard issues RFI as it considers arming vessels with high-energy lasers appeared first on DefenseScoop .

By Patrick Shortall Clifford Chance announced today (20th July) the deployment of a new knowledge management platform. The platform’s design was led by Epiq Advisory for Law Firms, the knowledge […] The post Clifford Chance pairs with Epiq Advisory and Microsoft for new knowledge management platform appeared first on Legal IT Insider .

Law librarians are 'uniquely positioned to wield influence' because their job is to help others, not to win. The post AALL 2026: An Aloha Keynote For Lasting Impact, Not Glitz appeared first on Above the Law .

[Sponsored] From advanced electro-optics and AESA radars to electronic warfare payloads and precision-guided munitions, ASELSAN is presenting a comprehensive portfolio designed to enhance the effectiveness of next-generation uncrewed platforms.

The regulator said it had "no further legal routes available" under the Online Safety Act.

The Italian prime minister said the deal is a “recognition of Italian defense industry but also of how Europe can reinforce its autonomy by investing in its own technological capacity and companies.”

An agentic AI infiltrated the production infrastructure of an AI project. Then an AI detected it. Is this the future of cyberattacks, and how will they be defended against?

Center for AI Standards and Innovation Director Chris Fall played a key role in the White House’s voluntary review of cutting-edge models.

The Times reports that the CMA's outreach is understood to be a precursor to a formal probe Source

There’s a prevailing principle in the U.S. that funding disparities are at the root of education inequality, with poorer districts receiving less money than their wealthier counterparts. But a recent study has actually found the opposite, documenting that over the past nearly 50 years high-poverty and predominantly non-white districts across all 50 states actually spent […]

The Investing Club holds its "Morning Meeting" every weekday at 10:20 a.m. ET.

[Sponsored] Some challenges show up no matter what industry you’re in. Contracting is one of them. The post 3 Contract Intelligence Use Cases Every Legal Team Should Know appeared first on Above the Law .

Remote access to domestic devices is increasingly being used to manipulate, intimidate and disturb. Policymakers and tech companies are grappling with safeguards. Von Emma Jacobs ( Security , Tracking )

The AI-powered robotic weapon, which weighs roughly 300 pounds and is capable of firing 850 rounds-a-minute, can detect and neutralize small unmanned aerial systems, Allen Control Systems said.

In government hiring, veterans’ preference is badly structured compensation that also fails on policy grounds. The post Cash out veterans’ preference in federal hiring, honor their debt appeared first on FedScoop .

Die Deutsche Telekom plant den Einsatz von 50G-PON als Nachfolger von XGS-PON. Erste Labor-Tests finden bereits statt, um die Netze f�r Multigigabit-Bandbreiten vorzubereiten. ( Telekom , Huawei )

The 2026 FIFA World Cup succeeded because millions of moving parts operated within carefully constructed legal frameworks that most fans never noticed. The post What The 2026 FIFA World Cup Taught Us About Global Events appeared first on Above the Law .

En el vídeo aparecen dos robots en un ring similar al de las peleas UFC. El cámara aleja el zoom y en ese momento uno de los robots lanza una espectacular patada circular y le da en toda la cabeza a su enemigo. Éste cae redondo como lo haría un humano.  Probablemente un humano no se levantaría tras un golpe así. El robot sí lo hizo.  Lo hace de una forma amorfa, muy de ciencia ficción, retorciéndose para que sus piernas vuelvan a permitirle hacerlo. La pelea continúa de una forma un po

AliExpress a l’insigne honneur d’écoper de l’amende la plus élevée jamais infligée par la Commission européenne dans le cadre du règlement sur les services numériques (DSA). La plateforme de commerce en ligne opérée par le groupe chinois Alibaba fait l’objet d’une sanction de 550 millions d’euros pour manquement aux obligations d’évaluation et d’atténuation des risques […]

Unidentified hackers compromised an online education system used by South Korea's diplomatic academy, stealing personal information belonging to former and current employees of the country's Ministry of Foreign Affairs.

David McGuinty said Canada’s planned F-35 purchase is still under review and will remain so “until we take the time to get it right for Canadians.”

Launch Africa has invested in 15 startups so far in 2026, with a focus on early-stage startups, as other investors slow down on funding.

Discovery's a bitch, man. The post Trump Bit Off More Than He Could Chew Suing BBC, So DOJ Will Chew It For Him appeared first on Above the Law .

Most AI chips are general-purpose. You load a model onto them, and they run it. Google is reportedly trying something stranger: a chip that is the model, with Gemini’s blueprint etched into the hardware itself. The project, informally called “Frozen v2,” was reported by The Information and picked up by Reuters and Bloomberg Law. Alphabet […] This story continues at The Next Web

Die EU-Kommission hat Leitlinien zur Kennzeichnung von KI-Inhalten verabschiedet. Ab August müssen Anbieter KI-generierte Inhalte transparent ausweisen.

U.S. Immigrations and Customs Enforcement has detained more than 650 children in California under President Donald Trump’s second term, an EdSource analysis of federal data has found. Most arrests happened in California communities, rather than at the border, and involved minors who resided and attended school in the state. The number of children detained in […]

AI companies can find vulnerabilities and write patches. But only the government can build the long-term defense strategy America needs. The post Why blocking AI models won’t stop the cyber threats they create appeared first on CyberScoop .

“There isn’t going to be a third reconciliation package. So anything that’s in there is not going anywhere,” said Sen. Jeanne Shaheen, D-N.H.

Asian shares are mostly higher but South Korea's Kospi has fallen nearly 5% as investors unload more stocks linked to artificial intelligence.

The commercialisation of artificial intelligence is poised to transition from a “token economy” to a “task economy” as token prices decline in the coming years, according to Chinese AI company SenseTime. “The pricing of tokens will inevitably drop, much like the cost of telecoms data did two decades ago,” SenseTime CEO Xu Li said in an interview with the South China Morning Post. After foundational models and computing power become basic infrastructure, the true commercial value will shift...

It may seem counterintuitive, but 113-degree water is still cool enough to cool NVIDA's latest hardware.

Banks are beginning to move beyond AI models that only score, classify, or recommend. The next wave ...

* After the Trump family and his administration prevailed upon Romanian officials to release suspected international sex traffickers, the Tate brothers are now set to be extradited to the UK. [ Forbes ] * Litigation funders getting squeezed on both sides. Some states have attempted to ban their work, and elsewhere investors are putting money behind law firms directly rather than work with a funder. [ Bloomberg Law News ] * ACLU gearing up to take on state surveillance tactics, which are much mor

Agentic commerce has reached checkout. Yet much of its control architecture still stops at permissio...

About half of voters believe it isn't appropriate for the U.S. government to own stakes in companies, a new CNBC poll found.

Alternative legal services provider QuisLex today (20 July) unveiled a new advisory framework designed to help legal departments and law firms build the institutional capability needed to produce AI-assisted legal work that […] The post QuisLex launches AI capability framework as focus shifts from adoption to accountability appeared first on Legal IT Insider .

InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants' own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul. By Artenisa Chatziou

Boomi, the data activation company for AI, today announced new research conducted by Forrester Consulting on behalf of Boomi showing that despite rapid enterprise adoption of AI agents, trust hasn't kept pace with ambition.

It would also make the use of copyrighted works to train AI models subject to fair-use limits or licensing agreements, Reuters reported. Source

Federal health officials have remained focused on lettuce from Taylor Farms as the source of a multistate outbreak despite inaccurate test results reported over the weekend.

More than 6 000 school projects will be on display at 38 regional fairs, with winners progressing to the Eskom Expo International Science Fair in September.

Millions of children are exploited in private video calls, exposing gaps in how platforms detect abuse and protect their youngest users.

La Comisión Europea publica las directrices sobre transparencia para sistemas de inteligencia artificial como los populares chatbots y para detectar ‘deepfakes’ que entrarán en vigor el 2 de agosto

'I thank FCC Chairman Brendan Carr for supporting our efforts and for his continued commitment to connecting households across our country to the Internet,' Thune said

Vamos a explicarte qué es Playwright y para qué sirve esta herramienta gratuita de código abierto. Con ella puedes hacer que un navegador web funcione solo sin que nadie lo toque, y es algo de lo que seguro has oído hablar en el contexto de la inteligencia artificial y los agentes de IA . Se trata de un elemento cada vez más presente en el mundo de la IA, y merece la pena conocerlo. Por eso, aunque no tengas conocimientos técnicos vamos a intentar explicártelo de una manera sencilla. Qué es Play

More than 250 million American adults start the new calendar year with a pledge to complete Dry January. By giving up alcohol for a month, some hope for a physical or mental reset, while others hope to give up drinking for good. While more than a quarter of participants won’t make it through the full […]

Here are five key things investors need to know to start the trading day.

Death Valley set a record when the temperature reached 134 degrees Fahrenheit. Here’s why deserts can reach such scorching temperatures – and also very cold ones.

History has shown that when manufacturers skimp on sterile filtration of drugs, the consequences can amount to the loss of hundreds of lives and millions of dollars.

Airtel allows hotspot use under its Unlimited 5G Data plan, with a 300GB fair-use limit. Detecting tethering may raise questions under India’s net-neutrality rules and about user privacy. The post How would Airtel detect hotspot use amid questions over its Unlimited 5G policy? appeared first on MEDIANAMA .

Most tech professionals wouldn't recommend their own role to someone entering the industry today.

La Selección Española nos ha vuelto a dar otro momento histórico para recordar con su 1-0 ante Argentina en la final del mundial, proclamándose por segunda vez campeona del mundo. Y lo curioso es que la celebración no solo se ha visto y oído, pues también se ha medido. El sismólogo Jordi Díaz Cusí, investigador de Geociencias Barcelona (GEO3BCN-CSIC), ha compartido en su cuenta de X una gráfica con los registros de la Red Sísmica Educativa del instituto durante la final entre España y Argentina.

Hugging Face reports an attack on parts of its production infrastructure that was allegedly carried out entirely by an autonomous AI agent system. The attack spanned thousands of actions controlled by an agent framework. During forensic analysis, commercial AI models actually got in the way of the defenders because their safety guardrails couldn't tell exploit data from real attacks. The article Hugging Face says an AI agent hacked its infrastructure, and it used AI to fight back appeared first

[Sponsored] GA-ASI will build Gambit aircraft in Europe, partnered with European-based companies, with airframes available for international procurement starting in 2027.

Financial services professionals caution that AI tools lack regulation, fiduciary duty and the contextual understanding needed for sound financial decision-making.

Ein Roboter k�pft den anderen in einer Kampfliga, die mehr Werbeveranstaltung ist. Man darf hoffen, dass das Modell nicht im Privathaushalt landet. ( Roboter , KI )

Over the past decade, the playbook for Nigerian fintechs has been remarkably consistent: build payment products, acquire merchants, scale transaction volumes, obtain microfinance bank licences, expand into lending, and eventually launch savings products.

Under the revised charges, published on the country’s electronic visa portal on Monday, Somali and Burundian citizens will pay $100 to enter South Sudan.

Viel hilft viel: Xiaomi hat mit �ber 100.000 Stunden Videomaterial ein KI-Modell f�r Roboter trainiert. Es soll das beste Open-Weights-Modell sein. ( Roboter , KI )

The three-month initiative aims to give university students practical workplace exposure before they graduate.

Bristol Myers Squibb is the third drugmaker in nine months to announce it is building the largest AI supercomputer in the life sciences industry.

Innenminister Dobrindt treibt eine radikale Reform des Nachrichtendienstrechts voran. Agenten des Verfassungsschutzes sollen sogar Wohnungen durchsuchen dürfen.

The company has completed a 0.88MWp solar project at its Component Plant, strengthening renewable energy generation.

Florida Republican congressman and governor's race candidate Byron Donalds has announced legislation intended to prevent artificial intelligence data centers from increasing utility costs.

Princess Moss has been a leader of the National Education Association since 2014, but soon she will implement her own plans for the union as incoming president. One of her top goals when she takes office Sept. 1 is to shift campaigning and organizing from the union’s centralized, national level to local affiliates. Moss was […]

Hugging Face hat einen von KI-Agenten ausgef�hrten Cyberangriff per KI entdeckt. Der Zugriff gelang durch Sicherheitsl�cken in der KI-Plattform. ( Cybercrime , KI )

Après l’amende de 150 millions d’euros infligée à Apple pour les modalités d’ATT, Le Figaro, L’Équipe et Adikteev réclament désormais réparation. Les trois entreprises estiment avoir subi un préjudice cumulé de 131,5 millions d’euros. Depuis iOS 14.5, livré en avril 2021, le dispositif de Transparence du suivi par les apps (ATT) a permis aux utilisateurs […]

The release of Kimi K3, an artificial intelligence model created by a former computer science graduate student at Carnegie Mellon University, has rocked parts of social media and the AI commentariat. The model, developed by Moonshot AI—a Chinese lab cofounded by that ex-student, Yang Zhilin—has wowed many observers with its capabilities. “Kimi K3 demonstrates the U.S. moat in building frontier AI software is not as durable as many of us had hoped,” says Ryan Fedasiuk, a fellow at the American En

Earlier this year, Tushar Sen, an independent researcher based in New Delhi, submitted a manuscript to Security and Privacy about the modeling of polymorphic malware. On May 15, a purported reviewer for the journal wrote Sen indicating he received the article, but that it was not ready for publication. “i may revise it with you … Continue reading Publisher investigating peer reviewer for alleged bribery scheme

The UBA Business Series brought together investors and entrepreneurs who...

The post Children in This Church Were Sexually Abused. Then They Began Abusing Other Kids. Some Continued as Adults. appeared first on ProPublica .

The Emerging Payments Association Asia (EPAA) has launched the AI & Agentic Payments Working Group with founding member HSBC, bringing together the banks, payment networks, fintechs and technology platforms that will define the standards to make agentic commerce work safely and at scale across Asia Pacific (APAC).

SCAORA opposes mandatory AI-use disclosures for lawyers, calling them unworkable. It also flags hallucinations, opaque AI systems, weak accountability, and risks to judicial data. The post Supreme Court lawyers’ body opposes mandatory AI disclosure in draft AI regulations appeared first on MEDIANAMA .

Un nouveau rapport de la banque des banques centrales analyse dans le détail les conséquences potentielles de la course à l’investissement dans l’IA. Il estime que le secteur est déjà en situation de surinvestissement, et que le mouvement en cours pourrait passer d’une « explosion » à un « effondrement » d’autant plus intense qu’il est financé par de […]

Startups operating in regulated or trust-sensitive sectors can now apply for VOVE ID's Compliance Infrastructure Program, designed to identify gaps in their onboarding, fraud prevention, and other compliance processes.

A humanoid robot combat event organized by a Shenzhen robotics company has gone viral, even catching the attention of Tesla CEO Elon Musk. On July 19, Musk reposted a video from the event on social media, writing, “Robot fights are fun.” The footage features two EngineAI T800 full-size humanoid robots trading punches and kicks inside […]

Also: All the news and watercooler chat from Fortune.

The forthcoming modifications follow concerns that the 747 jumbo jet rapidly modified by defense contractor L3Harris lacked security measures typical for transporting the US president.

Yimu Tech, a Chinese developer of tactile sensing hardware and software for embodied-intelligence systems, has completed a Series E financing round of more than RMB1 billion, bringing its valuation above RMB10 billion. The financing was jointly backed by multiple leading RMB funds, USD funds and industrial investors. The company is developing tactile sensing materials, chips, […]

Somewhere, a hard drive is filling up with secrets no one can read yet, and its owner is waiting for the machine that opens them all at once. On March 30, 2026, that wait got shorter.Two independent research teams lowered the public estimates for breaking the encryption that secures banking, communications, and classified traffic. One showed that Shor’s algorithm, the quantum method for factoring the large numbers behind public-key encryption, could run at cryptographically relevant scale with a

The secretary of defense’s November announcement on acquisition reform laid out an unprecedented vision across the entire acquisition spectrum to improve the delivery speed of critical capabilities to our warfighters. One foundational pillar is the implementation of a commercial first policy, which laid out several initiatives: leveraging existing but less often used acquisition authorities, maximizing non-traditional contract vehicles, and increasing the use of more flexible solicitations. Most

Driving More Students to ‘High-Value’ Programs Doug Lederman Mon, 07/20/2026 - 03:00 AM Defining programs solely by graduates’ earnings isn’t ideal, but it’s where we are. A new report shows that it can be done, and how. Byline(s) Doug Lederman

Inside the ‘Culture of Fear’ at One American-Chinese University Emma Whitford Mon, 07/20/2026 - 03:00 AM Faculty at Wenzhou-Kean have accused their employer of obfuscatory employment agreements, wrongful termination, discrimination, retaliation and lack of shared governance. University officials dispute the charges. Byline(s) Emma Whitford

New Initiative Targets Transfer Credit Loss Joshua.Bay Mon, 07/20/2026 - 03:00 AM Higher education accreditor SACSCOC’s new consortium aims to create common transfer pathways and shorten time to degree. Byline(s) Joshua Bay

How Soon Could Colleges Lose Loan Access Under New Accountability Metric? jessica.blake@… Mon, 07/20/2026 - 03:00 AM For most programs, data from the new test on student earnings will be released in 2027 and failing programs could face penalties in 2028. But some have been granted an extension that student advocates say is harmful. Byline(s) Jessica Blake

On Techpoint Digest, we talk about Kenya restoring the president's website after a hack, how fertility struggles led to a health startup, and Tinubu signing an executive order on virtual assets.

The Electoral Commission seeks virtualisation software licensing, privileged access management and mobile app development as elections draw near.

Netflix veut changer la manière dont l’engagement est perçu par les investisseurs et les observateurs. Dans l’esprit de la plateforme de streaming, une heure de compétition sportive diffusée en direct qui déclenche le recrutement d’un nouvel abonné a plus de valeur qu’une heure de programme regardée par un abonné fidèle. Plus de qualitatif, moins de […]

Une fois de plus, Apple et Google vont devoir supprimer de leurs boutiques des applications de génération de deepfakes. Le procureur municipal de San Francisco, David Chiu, a mis en demeure les deux contrôleurs d’accès de retirer 13 applications capables de produire des images à caractère sexuel truquées et sans consentement (huit sur l’App Store, […]

SEBI has warned regulated entities and listed companies about the "Boss Scam", in which fraudsters impersonate senior executives using deepfakes, voice cloning and malware to authorise fund transfers. The post SEBI warns of AI impersonation scams with fraudsters posing as company CXOs appeared first on MEDIANAMA .

Alle Infos auf der secIT digital: Ab September 2026 gelten die ersten Vorgaben des CRA. Das IT-Sicherheitskonzept Grundschutz++ soll 2026 finalisiert werden.

China has developed more than 400 humanoid robot products, accounting for more than half of the global total, according to data released by the Ministry of Industry and Information Technology on July 20. The ministry also said Chinese quadruped robots accounted for close to 70% of global sales. [Xinhua, in Chinese]

Bilibili showcased its open-source “Catgirl Plan” AI digital-life ecosystem at WAIC 2026 in Shanghai on July 18. Its core product, Project N.E.K.O., is a proactive multimodal AI companion that can continuously observe a computer environment, interpret desktop content and initiate conversations. The system separates its front-end interface, AgentAI system and memory layer, while allowing users […]

Join our invite-only New Delhi roundtable on age verification, children’s social media access, enforcement challenges, and policy alternatives to blanket restrictions in India. The post Agenda: Age Verification and Restricting Social Media for Children, Delhi, 31 July #NAMA appeared first on MEDIANAMA .

China’s market regulator is poised to announce the outcome of its months-long antitrust investigation into Trip.com Group, the country’s largest online travel services provider, as soon as this week, according to three people familiar with the matter. The probes, launched in January by the State Administration for Market Regulation (SAMR), could be concluded as early as Monday, one of the people said. The company could face a fine of between 2 billion yuan (US$295 million) and 6 billion yuan,...

Speaking in an interview with CNBC, TSMC's Wendell Huang said the fresh investment comes on the back of robust customer demand.

The deal size will exceed Luxshare Precision's $3.1 billion IPO earlier this month, making it the largest listing in Hong Kong this ​year.

Brian Yasko, managing director at Accenture and Emma Harmon, co-CEO of Whalar, on the massive creator economy acquisition and future plans.

As AI supercharges cyber threats, organisations face multiple challenges: a new breed of reckless western hackers trying to impress their peers; fake remote workers attacking from the inside; and supply-chain weaknesses

Hacking groups behind attacks on UK organisations reveal how the profile of criminals is changing

AI-powered cyber crime is raising the stakes for companies — but what do insurance policies actually offer?

Infiltrating one organisation in the network can open up access to hundreds more

Use of AI deepfake employees to infiltrate companies highlights wider risk of internal security breaches

Criminal groups are building deepfake personas on an industrial scale to trick people into divulging information

Could also impact HR's use of AI.

To be led by Attorney-General.

Ariane Gorin faces battle with tech start-ups as she repositions world’s second-largest travel booking company

In this edition of After Hours, we follow the journey of Victoria Duru, and how her personal experience balancing childbirth and work inspired her startup, Wakamedics.

At the 2026 World Artificial Intelligence Conference (WAIC), Honor CEO Li Jian unveiled the company’s first Robot Phone, confirming it will launch globally in August with pre-orders now open across all sales channels. The device is powered by Qualcomm’s latest Snapdragon 8 Elite Gen 5 platform and features a 1.5K flat display with ultra-narrow, symmetrical […]

Israel’s military destroyed a residential building in Deir Al-Balah, central of Gaza Strip after ordering people to flee their houses, residents said.

Massive investment plans lead to investor fears of a new boom and bust in memory chips

Cloud-native banking platform Lumin Digital has raised over $70 million in new capital from its own clients.

At Shanghai’s World Artificial Intelligence Conference, tech companies showcased phones designed to understand user intent and coordinate tasks across services.

The singularity will be seen in hindsight as an interregnum

OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.

Are you a California resident? Then we've got exciting news for you: there's a tool just for you that lets you take a single, relatively easy step to protect your privacy. It's called a DROP request. (That's Delete Request and Opt-out Platform, if you're fancy). This one bit of paperwork lets you tell every data broker registered in the state of California that you'd like them to delete your information from their databases and request they stop selling and sharing your information. Here are som

A new report from the Government Accounting Office reveals that the Department of Homeland Security (DHS) plans to nearly triple the number of surveillance towers along U.S. borders, from the current 830 to 2,300 by 2034. DHS expects to expend $1 billion in taxpayer dollars for this dangerous expansion of a surveillance network indiscriminately trained on towns, school playgrounds, backyards, and vehicles—threatening the privacy and civil liberties of everyone in the border regions. The towers a

There’s a new boogeyman in the battles over AI: so-called “stealth crawlers.” We’ll admit it—the term “stealth crawlers” sounds quite nefarious. In reality, they’re anything but. “Stealth crawlers” are simply automated tools to access and collect public web data—without disclosing the user’s identity. Private crawlers like these facilitate all kinds of important work that benefits the public, including investigative reporting, academic research, cybersecurity protection, and more. Anonymous craw

Rapidly growing agetech industry has a significant opportunity to close trust gap, increase product adoption with increased transparency WASHINGTON, D.C. — (July 20, 2026) — The Future of Privacy Forum (FPF) — a global non-profit focused on data protection, AI, and emerging technologies — today released findings from a comprehensive March 2026 survey about how […]

Greetings from a world where…

I keep hearing anecdotes from people who used coding agents to reverse-engineer and automate devices in their homes. I think this is an interesting illustration of the impact of the reduced cost of writing code. Prior to agents, it was entirely possible to reverse-engineer home devices. The problem was the ROI - was it really worth all of that effort? More importantly, any experienced programmer knows that undocumented, unstable APIs like that may well change or break in the future. Is that init

Europe wants its own technology champions. It just seems less comfortable with what champions look like once they arrive. The European Commission’s latest Digital Markets Act (DMA) decisions capture that tension. Europe wants more innovation, investment, and globally competitive digital platforms. Yet when a company assembles the data, technology, distribution, and complementary services needed to ... Europe Wants Tech Champions, Then Makes Them Share the Trophy The post Europe Wants Tech Champi

Who’s Afraid of Chinese Models? Interesting proposal from Ben Thompson that both addresses the hypocrisy of labs outlawing distillation against their models despite training on unlicensed data, and could help US open models compete more effectively with their Chinese counterparts: The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service that forbid distillation, for U.S. companies at a minimum. Stopping distillation —

The global threat environment in 2026 is the darkest since the Cold War—active conflicts on three continents, an aggressive Russia, and a rapidly modernizing Chinese military. Yet the exhaustion of ...

Extremophiles that thrive in the most unforgiving environments aren’t just biological curiosities. Understanding their resilience has many implications for us. The post The Organisms That Make Earth’s Harshest Places Home first appeared on Quanta Magazine

From open models to real-time simulation, AI and graphics breakthroughs are transforming media, content creation and robotics.

A detailed record of federal courts and grand juries rejecting the Trump administration’s use of subpoenas, search warrants, and indictments. The post “Zero Evidence”: How Judges and Grand Juries Have Rejected the Trump Administration Efforts to Investigate and Prosecute appeared first on Just Security .

These EU AI Act provisions will start to apply on August 2 | Edition #307

Data centers have become a kind of boogeyman among voters lately. Recent polling even suggests that new data center construction is less popular than the IRS. Only 27% of Americans at least somewhat ...

Signup to receive the Early Edition in your inbox here. A curated guide to major news and developments over the weekend. Here’s today’s news: IRAN WAR The Pentagon said yesterday that a third member of the U.S. military had died over the weekend during the disposal of a downed Iranian attack drone in northern Iraq […] The post Early Edition: July 20, 2026 appeared first on Just Security .

A recent story of a writer who was mistakenly identified, tracked, and arrested using data from Flock cameras has gone viral. The New Jersey plates that were allegedly stolen from the LA dealer were 34 03 DTM , not 34 10 DTM . But when the police report was created and the plate was entered into Flock’s system, it was just recorded as 34 DTM . Just the five large characters, no little number in the middle. And Flock’s AI tech wasn’t registering that non-standard little number when it began picki

Erin Davis calls it the “SuperDuperPOD.” That’s two things in one name: pharmaceutical giant Bristol Myers Squibb (BMS) already runs one of the largest AI clusters in life sciences, with serious results to show for it. And they’re doubling down. BMS announced today it is deploying its second NVIDIA DGX SuperPOD, this one built on […]

WASHINGTON – The American Civil Liberties Union today kicked off its largest ever National Advocacy Institute, hosting over 900 students from all 50 states, Washington, D.C., and Puerto Rico in the ...

On Wednesday 15 July 2026, the Court of Appeal (Vos MR, Warby LJ and Whipple LJ) handed down judgement in the appeal of Vince v ANL [2026] EWCA Civ 899. Eco entrepreneur, Dale Vince brought a defamation and subsequent data protection claim against Associated Newspapers in relation to the publication of an article which juxtaposed […]

4th IEEE International Conference on Medical Artificial Intelligence [Zhengzhou, China] [Nov 20, 2026 - Nov 22, 2026]

Long video summarization presents significant challenges for multimodal large language models (MLLMs), particularly in maintaining temporal fidelity over extended durations and producing summaries that are both semantically and temporally grounded. We introduce LVSum, a human-annotated benchmark for evaluating long-form video summarization with fine-grained temporal alignment. LVSum comprises 72 diverse videos spanning 13 domains with an average duration of 16 minutes, each annotated with up to

Digital Talent EU Days 2026 in Dublin Anonymous (not verified) Mon, 07/20/2026 - 15:02   15 October 2026 - 16 October 2026   Trinity Business School, Dublin, Ireland The Digital Talent EU Days will host a debate on Europe’s digital skills challenges and drive action on talent, competitiveness and inclusion. Digital Talent EU Days On 15 and 16 October, LEADSx2030 and Connecting Women in Digital , in partnership with the European Commission, National Coalitions , agencies and local partn

Commission publishes guidelines on transparency obligations for providers and deployers of certain AI systems Anonymous (not verified) Mon, 07/20/2026 - 09:08 Today, the European Commission published guidelines to assist providers and deployers of artificial intelligence (AI) systems in meeting the AI Act's transparency obligations, which start to apply on 2 August 2026. Transparency obligations will help people recognise when they are interacting with AI or when content has been generated or al

Guidelines on transparency obligations for providers and deployers of AI systems Anonymous (not verified) Mon, 07/20/2026 - 08:58 These guidelines define the scope of transparency obligations for providers and deployers of AI systems under article 50 of the AI Act. The AI Act follows a risk-based approach, classifying AI systems into four different risk categories, one of which is AI systems posing transparency risks that are subject to the obligations laid down in Article 50 of the AI Act . The

BY THE PRESIDENT OF THE UNITED STATES OF AMERICA A PROCLAMATION 1. Section 338 of the Tariff Act of 1930 (19 U.S.C. 1338) (section 338) empowers the President to, among other things, impose duties on imports of a foreign country to offset the burden or disadvantage from a foreign country’s discrimination against or unequal imposition […] The post Imposing Additional Duties to Offset Canadian Discrimination Against the Commerce of the United States with Respect to Motor Vehicles appeared first on

BY THE PRESIDENT OF THE UNITED STATES OF AMERICA A PROCLAMATION 1. Section 338 of the Tariff Act of 1930 (19 U.S.C. 1338) (section 338) empowers the President to, among other things, impose duties on imports of a foreign country to offset the burden or disadvantage from a foreign country’s discrimination against or unequal imposition […] The post Imposing Additional Duties to Offset Canadian Discrimination Against the Commerce of the United States with Respect to Alcoholic Beverages appeared fir

BY THE PRESIDENT OF THE UNITED STATES OF AMERICA A PROCLAMATION 1. Section 338 of the Tariff Act of 1930 (19 U.S.C. 1338) (section 338) empowers the President to, among other things, impose duties on imports of a foreign country to offset the burden or disadvantage from a foreign country’s discrimination against or unequal imposition […] The post Imposing Additional Duties to Offset Canadian Discrimination Against the Commerce of the United States with Respect to Dairy appeared first on The Whit

By the authority vested in me as President by the Constitution and the laws of the United States of America, it is hereby ordered: Section 1. Policy. The United States military is the most effective and powerful fighting force on the planet. It fields the most advanced weapons systems and technologies in the world, utilizing […] The post Securing America’s Defense Supply Chains and Ensuring Domestic Acquisition of Critical Materials appeared first on The White House .

BY THE PRESIDENT OF THE UNITED STATES OF AMERICA A PROCLAMATION For two and a half centuries, America’s proud legacy has been shaped by visionaries and builders who have chased excellence and reached for the impossible. During Made in America Week, we celebrate the mighty engine of American manufacturing, driven by the businesses and workers who power our economy, and recommit to building a future where our greatest works are yet to come. American craftsmanship has long […] The post Made in Amer

The National Institute of Standards and Technology (NIST or Institute) invites and requests nomination of individuals for appointment to seven existing Federal Advisory Committees (Committees): Advisory Committee on Earthquake Hazards Reduction; Board of Overseers of the Malcolm Baldrige National Quality Award; Information Security and Privacy Advisory Board; Manufacturing Extension Partnership Advisory Board; National Artificial Intelligence Advisory Committee, including the National Artificial

The Commodity Futures Trading Commission (CFTC or Commission) is publishing this notice to announce the renewal of the Agricultural Advisory Committee (AAC). The Commission has determined that the renewal of the AAC is necessary and in the public's interest.

The United States Trade Representative (Trade Representative) has determined under Section 301(b) and Section 304(a) of the Trade Act of 1974, as amended (Trade Act), that certain of Brazil's acts, policies, and practices at issue in this investigation are actionable and that action by the United States is appropriate. In accordance with the specific direction of the President, the Trade Representative is taking action by imposing 25 percent tariffs on all imports of Brazil, with certain exempti

The CNIL’s recommendation of 12 March 2026, which was published on 14 April 2026 and applicable from that date, provides detailed guidance on the legal framework applicable to email tracking pixels. While the applicability of ePrivacy rules to tracking pixels had already been recognised at European level, notably through the EDPB’s interpretation of Article 5(3) [...] The post France: Email Tracking Pixels — What the CNIL’s Recommendation Changes in Practice appeared first on Connect On Tech .

Artificial intelligence can boost productivity, create better jobs, and improve public services in sub-Saharan Africa, but realizing these gains will require reliable power, affordable internet, ...

Why This Matters The Office of Personnel Management (OPM) is the federal government's central agency for human resources and workforce management. Since December 2024, in alignment with presidential directives on the closure of certain offices and the reduction of the size of the federal workforce, OPM has undergone significant workforce and organizational structure changes. These actions have reduced institutional knowledge and operational capacity at the agency. OPM’s Headcount Decreased by 35

Online seminar series on Water for all people: equal rights and opportunities - Cat VII – Seminar and training ...

In brief On 2 February 2026, Saudi Arabia issued Royal Decree No. M/169 approving a new Copyright Law, by virtue of Cabinet Decision No. 560/1447 dated 27 January 2026. The Law was published in the Official Gazette on 13 February 2026 and will enter into force on 12 August 2026, replacing the 2003 Copyright Law [...] The post Saudi Arabia: New Copyright Law Modernises KSA IP Framework appeared first on Connect On Tech .

Discourse relations provide document structure, critical to language understanding and enabling language model performance and ethicality. In this work, we investigate how instruction-tuned Transformer models (LLaMA and Mistral) encode discourse relations in English, with a particular focus on the contrasting relations of causation and antithesis. Framing the task as a next-token prediction task and applying a suite of interpretability techniques to test model internals, our findings show that c

A graph foundation model generalizes across graph domains by mapping every input into one shared representation before any task reasoning. We call this map the alignment layer, the component that separates a graph foundation model from a graph neural network, and we show it is a distinct attack surface that prior work has not studied. We attack it at inference time, with no access to training, on six public models spanning spectral tokenizers, text embedding spaces, and a discrete codebook. A di

Macro placement still requires substantial manual refinement in industrial physical design flows. We present MAGE (Macro Placement Agentic Engine), a multimodal multi-agent framework for macro placement refinement. MAGE decomposes the macro placement task into a six-phase workflow that combines structured floorplanning rules, visual checks, and iterative refinement. Expert floorplanning knowledge is encoded through natural-language directives and validation criteria, rather than learned from lab

AI alignment is essential for the safe deployment of advanced AI systems. Given that values and preferences change over time, culture, social roles, and context, we need to develop a better understanding of the possible long-term consequences of AI alignment, in particular considering the likely ubiquitous future use of personalized AI assistants. We introduce a flexible and extensible mathematical modelling framework, rooted in social physics, aimed at answering macro-level questions regarding

The digital substrate of states -- data, algorithms, infrastructure, platforms, applications -- is being governed without adequate conceptual foundations. The ability and legitimacy required to govern this substrate, and to govern with it, are simultaneously misaligned, contested, and structurally absent. We introduce digital statecraft as the organising concept for this emerging field, arguing that 'digital' reconstitutes the statecraft question rather than merely extending its domain. The conc

Group Relative Policy Optimization (GRPO) has shown strong effectiveness in reinforcement learning from verifiable feedback, where sampled rollouts can be compared within a group using task-provided correctness signals. However, extending group-relative optimization beyond verifiable settings is challenging because success in many tasks is not captured by a single correctness criterion. We propose \textbf{Reference-Relative Policy Optimization (RRPO)}, which generalizes GRPO by replacing direct

The rapid improvement of AI systems has intensified debate about humanity's economic, political, social, and existential future. As AI reshapes expectations about what lies ahead, policy choices and institutional responses will play a crucial role in determining who benefits, who bears the costs, and whether the most serious risks can be mitigated. Africa remains relatively overlooked in these discussions, partly because it is largely a consumer rather than a producer of frontier AI systems, and

Unlike conventional video game development, which relies on labor-intensive pipelines for asset production, animation, physics, and programming, video world models generate interactive environments from user inputs instantly. It enable us to create customized, explorable, and continuously evolving virtual world from text, an image, or video. Realizing this vision requires four tightly coupled capabilities: interaction, persistent spatiotemporal consistency, stable long-horizon generation, and ef

The integration of general-purpose artificial intelligence models into downstream AI systems, among other developments, has given rise to new forms of risk that are more systemic in nature than conventional AI risks. However, there is no generally accepted definition of systemic risks in general and for AI in particular. Conceptualisations of these risks vary across research and regulation. Especially the application of the systemic risk approach to human rights or fundamental rights, like in th

Large language models (LLMs) serving as planners in tool-using autonomous agents introduce dynamic reliability risks in multi-turn execution. While single-turn safety mechanisms are relatively mature, extended interactions reveal structural vulnerabilities where initial alignment degrades over time. This paper empirically characterizes two observed failure modes across multiple state-of-the-art LLMs: Safety Drift, the gradual erosion of declared safety intent leading to constraint-violating acti

Modern LLMs are alarmingly susceptible to surprisingly simple immaterial changes of input prompts: a casual hint, an incorrectly labeled few-shot example, or a fake prior assistant turn often flips an originally correct answer. We study where this susceptibility, spanning sycophancy and related cue-induced biases, lives inside the model. Across five model families and seven BCT bias types, we extract a per-bias direction from hidden states and triangulate it through three measures: probing, leav

Generative models trained on a source domain often produce samples that are poorly aligned with shifted target domains, limiting their effectiveness for target-domain data augmentation. Although target-specific adaptation can reduce this mismatch, it typically requires additional optimization and domain-specific parameters. We propose a Similarity-based Generative Network (SGN), a reusable framework that is trained once on labeled source data and applied to new target domains without parameter u

Coding agents can now be left alone to improve software against a score. In this pattern--recently popularized as "autoresearch"--the agent receives a dataset, an evaluation script, and one editable file, and iterates without supervision: modify the code, measure, keep the change if the score improves. But what does the agent actually optimize--the developer's intent, or the literal number? We ran this loop on a real production task: deciding which Quranic verses appear in a noisy speech-recogni

End-to-end vision-language navigation (VLN) with causal vision-language models can map instructions and egocentric observations directly to actions, but standard behavior cloning supervises only the next action and does not explicitly train the policy state to be predictive of future visual outcomes. We first ask a diagnostic question: if the policy is given an expert-trajectory future image as privileged input at training and testing time, is that additional visual evidence useful for choosing

Can large language models with substantially different parameter spaces be merged by direct weighted averaging, without training or semantic alignment? Existing heterogeneous fusion methods typically introduce distillation, adapters, learned latent spaces, routing, or feature alignment, leaving open whether a simpler recipe can work for genuinely different billion-parameter checkpoints. We revisit this counterintuitive question through training-free dimensional adaptation followed by ratio-contr

Large language models (LLMs) can assist GPU kernel generation, but their practical effectiveness depends on whether generated code can be reliably constrained, validated, profiled, and selected. This paper presents a harness-centered system for LLM-driven GPU kernel optimization in the MLSys 2026 FlashInfer AI Kernel Generation Contest on NVIDIA Blackwell B200 GPUs. The system separates an evaluation harness from a profile-backed optimization controller: the harness enforces compilation, correct

Large Language Models (LLMs) often struggle to navigate value conflicts when trained with the compressed scalar rewards of Reinforcement Learning from Human Feedback (RLHF). To address this challenge, we investigate how chain-of-thought (CoT) reasoning can help improve performance in this domain. Geometrically, we show that CoT correlates with further smoothing the model's loss landscape in its sharpest direction, helping resolve the optimization instability of traditional scalar rewards. We als

This paper frames Generative Artificial Intelligence (AI) not as an unprecedented technological rupture, but as an industrial-scale manifestation of a deeply rooted historical process. Through a genealogy of generative arts, it shows how AI's questions on authorship and creativity have precise historical precedents. A taxonomy of generative systems is proposed across three functional categories (medium, artwork, instrument), the attribution of which is editorial rather than ontological. From ind

While Root Mean Square Normalization has become the de facto standard for accelerating modern sequence models, its reliance on the quadratic accumulation of independent scalars ($\sum x^2$) inherently triggers outlier-induced numerical instability, gradient starvation, and anisotropic phase distortion. We introduce Mean Root Square Normalization (MRSNorm). By structurally pairing channels into 2D phasors, MRSNorm mathematically inverts the traditional scaling paradigm: it computes the localized

Accurate 3D--2D liver registration, which aligns preoperative 3D models to partial, view-dependent intraoperative surface observations, is critical for AR-guided laparoscopic surgery but remains challenging due to severe occlusion, limited visibility, and the lack of 3D ground-truth supervision. Existing landmark-free approaches perform partial-to-complete geometric alignment, yet robust self-supervision under extreme partial visibility remains difficult. We propose Vis2Reg, a visibility-aware r

Vision-Language Navigation (VLN) requires an embodied agent to interpret a natural-language instruction and predict actions from temporally ordered visual observations. Adapting a multimodal large language model to VLN requires visual-language alignment, compact temporal inputs, action-space grounding, and stable training on the target hardware. This technical report presents PGN (Pangu Navigator), an offline VLN action-prediction system built on OpenPangu-7B. Training proceeds in two stages. Fi

Financial statements (FS) such as Balance Sheet (BS), Income Statement (IS) and Cash-flow Statement (CS) summarize the annual financial performance of a company. FS are widely used for evaluating corporate governance, credit appraisal, risk analysis, validate taxation, make investment decisions etc. Financial auditing is a complex and knowledge-intensive discipline whose one important aim is ensuring integrity, accuracy, fairness and absence of material misstatement in the published FS. Given th

Does adding a reasoning step make a Vision-Language-Action (VLA) model more robust to perturbation? Intuitively, a policy that reasons before acting should absorb a perturbed input better than one that maps observations directly to actions. We test this premise head-on across three models that span the reasoning spectrum (no reasoning, a text chain-of-thought, and a latent iterative loop), perturbing each at the vision, reasoning, and action stages on LIBERO and SimplerEnv. Two questions organiz

Cyber-physical systems built on deterministic edge inference, such as on-vehicle flood detection for agricultural fields, produce structured decision logs that must be interpreted differently by heterogeneous stakeholders. Pairing such systems with large language models (LLMs) to generate stakeholder-specific reports introduces a tension: the generative layer is non-deterministic, while the edge plane must remain replayable and auditable. We propose an architectural pattern resting on two invari

Within Explainable Artificial Intelligence, mechanistic interpretability uses Sparse Autoencoders (SAEs) to extract more interpretable features from neural representations. However, assessing their monosemanticity, and thus explanation quality, remains challenging. Existing metrics require external concept labels or depend on pretrained embedding models, making them sensitive to encoder's geometry. We introduce the Tversky Monosemanticity Score (TMS), a label-free metric that operationalizes mon

Recently, speech deepfake detection (SDD) has achieved significant progress. However, its robustness evaluation remains largely confined to controlled additive noise scenarios, lacking systematic investigation of the complex distortions introduced by acoustic front-end (AFE) processing pipelines in real-world deployments. In this work, we simulate a unified AFE pipeline comprising acoustic echo cancellation, noise suppression, automatic gain control, and voice activity detection (VAD), and condu

User experience is a first-class objective in industrial e-commerce recommender systems (RS). Post-ranking strategies, which govern diversity, similarity, and exposure over a ranked list, are widely deployed in industrial RS for their simplicity and low serving cost. However, as the online recommendation environment evolves continuously, these statically configured strategies gradually become stale, degrading the user experience. Refining them typically relies on manual inspection, diagnosis, an

Detecting high-level semantic concepts like negation across modalities remains a challenge for current multimodal systems. We analyze this as a fundamental representation learning problem, providing the first evidence that negation does not form a linearly or non-linearly separable class in the latent spaces of standard vision-language models (VLMs). We demonstrate that pretrained embeddings primarily encode modality-specific features, lacking a generalizable negation signal. To overcome this, w

Urban transportation systems generate heterogeneous data, yet these data do not automatically become actionable management intelligence. This chapter adopts a behavior-centered perspective on artificial intelligence (AI), treating mobility records and passenger-generated text as behavioral evidence rather than behavioral truth. It examines four directions: bus arrival prediction for service reliability, taxi mobility pattern discovery for demand analysis and planning, abnormal behavior detection

Modern software teams have mature tools for low-level testing, such as pytest, JUnit, and Jest, which make it inexpensive to write unit tests and run them on every commit. Systems engineering, in parallel, has developed rigorous principles for design verification and validation (V&V), which has worked very well across engineering discipline to align user expecations and requirements with developers' deliverables. In practice, however, the two rarely connect, and the link between users' high-leve

A language model $p_θ(y \mid x)$ trained on reasoning tasks learns to solve problems via multiple distinct strategies, yet these strategies are implicit and entangled within the model's response distribution. We study the problem of decomposing the response distribution of a given pretrained language model into a structured, strategy-conditioned representation. Specifically, we learn a latent-variable factorization $p_θ(y \mid x) \leadsto (r_φ(z \mid x), g_φ(y \mid x,z))$, where a router $r$ map

Contrastive learning is increasingly moving toward settings with three or more modalities instead of image-text pairs. Yet, extending models from pairwise to higher-order multimodal alignment can introduce optimization and representation challenges. We identify encoder Jacobian conditioning as a key factor in trimodal contrastive learning: poorly conditioned encoders exhibit collapsing or amplified singular-value spectra, leading to exploding Jacobian condition numbers and degraded multimodal al

Unsupervised Graph Domain Adaptation (UGDA) aims to facilitate knowledge transfer from a labeled source graph to an unlabeled target graph by mitigating cross-domain distribution shifts. Existing methods primarily focus on node-level feature alignment in latent spaces, relying on the implicit assumption that all source nodes contribute positively to the alignment. However, this assumption often fails because a node's semantic information is intrinsically coupled with its topological graph struct

Multimodal large language models (MLLMs) still struggle with spatial reasoning that requires perspective transformation. In particular, they often rely on camera-centric cues rather than reasoning from the reference object's viewpoint, leading to systematic errors in non-camera reference settings. In this paper, we first analyze this failure mode and show that object orientation is a key factor underlying such camera-centric shortcut behavior. To address this issue, we propose OrientSAM, an orie

Verify-repair loops are a standard means for large language model (LLM) agents to correct faulty plans in code generation, mathematical reasoning, and tool use. When both the verifier and the repairer are noisy, repair can damage already-correct plans, and reported acceptance keeps rising while true validity falls, so existing methods lack a principled basis for deciding when repair should stop. We propose VRR-Stop, a robust stopping framework for noisy verify-repair-repeat (VRR) loops. A four-p

Recent advances in world models and video generation have given rise to an emerging reasoning paradigm that leverages video generative models to simulate, predict, and reason about real-world dynamics. We redefine this paradigm as Thinking in Video, where video is not merely an output artifact but a medium for constructing, extending, and verifying causal thought. However, this promise remains unverified: convincing rollouts may reflect memorized appearances rather than causal understanding, whi

Direct feedback alignment (DFA) trains hidden layers with fixed random projections of the output error, avoiding the transposed-weight backward pass of backpropagation (BP). We study a failure mode of DFA training that is distinct from feedback quality: the local weight update is calculated by an outer product, so anisotropy can enter through either its presynaptic-activity factor or its local-error factor. Our analyses with controlled synthetic regimes isolate the first failure mode and show an

Amid accelerating digital health transformation, China has developed a centrally coordinated data-driven healthy China pathway. This viewpoint conceptualizes this pathway as a hybrid continuous planning framework (HCPF) that links long-term strategic direction with short-cycle tactical adaptation. China’s strategy has progressed through 3 overlapping periods: infrastructure-oriented periodic planning (2015-2018), emergency-driven digital acceleration (2019-2021), and institutionalized continuous

Background: Depression, anxiety, and posttraumatic stress disorder (PTSD) are leading global causes of disability. Standard interventions have slow mechanisms of action, high attrition, and significant accessibility barriers. While intravenous and intranasal ketamine are rapid-acting alternatives, high cost and intensive logistical requirements limit adoption. Sublingual at-home ketamine addresses some gaps but is constrained by low bioavailability and variable absorption. Subcutaneous administr

Background: Patients with prostate cancer undergoing androgen deprivation therapy (ADT) must manage complex treatment side effects over extended periods outside the hospital, making online health information–seeking a key approach to self-management. However, individual differences in motivation, digital literacy, and psychosocial context significantly influence how patients seek and use online health information. The patient persona approach, which synthesizes individuals with similar behaviora

Text-to-image diffusion transformers (DiTs) jointly process text and image tokens, yet their internal computation during denoising remains poorly understood. We introduce a causal interpretability framework for modern large-scale DiTs that combines attention decomposition with targeted interventions across token spans, heads, and layers. Using it to separate prompt-content tokens from structural template tokens, we find that the structural tokens carry little prompt-specific information at the e

Asynchronous reinforcement learning improves throughput by decoupling rollout generation from optimization, but staleness is an inevitable byproduct compounded by policy lag, engine delays, and mixture-of-experts routing. From a trust-region perspective, this mismatch is critical: training-inference divergence governs approximation error in finite-horizon bounds, whereas PPO clipping only gates sampled outward updates, acting as a sampled surrogate rather than a full-policy constraint. As a resu

Video models absorb rich priors over how the visual world moves, interacts, and responds to contact, making them promising substrates for robotic world modeling. The central challenge is how to communicate action to such models in a form aligned with the visual space in which they learned these interaction priors, yet still grounded in physical manipulation. We introduce Masked Visual Actions, a pixel-space control interface that expresses action as a partially revealed trajectory of an arbitrar

Reinforcement learning with verifiable rewards (RLVR) has substantially improved the reasoning capabilities of large language models on tasks such as mathematical reasoning and code generation. However, most RLVR methods assign a scalar outcome reward to an entire trajectory, resulting in sparse supervision and limited token-level credit assignment. On-policy distillation (OPD) provides denser supervision by distilling token-level distributions from a stronger teacher model, but requires an addi

Scaling executable agent training data for LLM post-training is bottlenecked by substrate-bound methods that tie task generation to predefined tools, repositories, or skill graphs: expanding coverage requires manual substrate engineering, each new domain demands a bespoke pipeline, and the resulting task distributions often reflect substrate biases rather than real-world demand. We introduce NexForge, a requirement-driven framework that takes high-level capability requirements as input and synth

We present AutoIndex, a framework for learning representation programs: executable transformations that map raw documents into the representations exposed to a retrieval system. Rather than tuning retrievers, rerankers, or a small set of preprocessing hyperparameters, AutoIndex searches over programs that slice, enrich, normalize, reweight, or reorganize documents before indexing. At each iteration, AutoIndex performs validation-guided program search, in which agents diagnose failures of the cur

Modern ASR models trained on heterogeneously annotated data treat transcription style (verbatim vs. intended) as an uncontrolled latent variable, causing measurable decoding instability, evaluation confounding (up to 60% of reported WER attributable to style mismatch), and unreliable word-level timing. We show that models already encode both styles; the challenge is controlled activation. Using coverage-aware decoder task tokens trained on parallel verbatim/intended transcript pairs, we raise Ge

Accurate agricultural field boundary delineation at large scale is a foundational task for food security, supply chain transparency, and carbon accounting. While vision foundation models like SAM show remarkable zero-shot capabilities, they frequently fail in geospatial domains due to topological complexity, cropland texturing patterns, and a lack of physical scale awareness. In this work, we introduce Delineate Anything v2, a globally scalable foundation model designed specifically for wide-are

LLM agent failures are difficult to debug because the step where an error surfaces is often not the one that caused it. Existing observability tools replay execution traces but provide little support for identifying the root cause or translating diagnosis into recovery. We present AgentDebugX, an open-source debugging framework that organizes debugging as a closed loop of Detect, Attribute, Recover, and Rerun. At its core, DeepDebug performs multi-turn root-cause diagnosis through global traject

Agentic Reasoning has become a transformative force in financial analysis due to its ability to integrate large-scale information and generate reliable and accurate content. However, when handling complex real-world problems, different agents still show significant performance variation. In this work, we design Finance-LaTeX SKILL, a skill for synthesizing financial documents with complex layouts based on expert knowledge. Using an agent workflow built on this skill, we generate 2,000 profession

Background: AI is rapidly transforming medical practice, with emerging applications in perioperative care and anesthesiology. However, the clinical implementation of AI-assisted decision-making systems in anesthetic management remains challenging and requires comprehensive evaluation. Objective: This study aimed to assess the performance and clinical applicability of an AI-assisted decision support system (ZW-AA-001) for general anesthesia management by comparing its decisions with those of expe

Background: The use of social media (SoMe) during crisis and disaster situations (CaDs) has gained increasing attention across disciplines. However, existing research is highly fragmented and often focused on technical aspects, with a limited understanding of how and which psychosocial information is derived from SoMe in CaDs. Objective: This scoping review provides an overview of the current research landscape regarding the analysis of SoMe data during CaDs to obtain information about public me

Background: Black communities face disproportionate burdens of health disparities such as chronic disease, maternal morbidity, and barriers to accessing quality care. Digital health technologies (DHTs) are increasingly promoted as tools to reduce health disparities through access to care. However, the extent to which equity-oriented design approaches have been applied to address the needs of Black communities remains unclear. Objective: This scoping review aims to examine (1) current literature

Background: Health literacy is crucial for pregnancy outcomes; yet, 15%-44% of pregnant women have low health literacy, negatively affecting maternal and fetal health. While pregnancy apps are increasingly used to support it, the psychological mechanisms through which they influence behavior remain unclear. Understanding these mechanisms is essential for designing effective interventions. Cognitive load theory (CLT) and the integrated model of cognitive-affective learning with media (ICALM) prov

This paper considers a multi-environment factor model in which high-dimensional covariates are collected from heterogeneous environments, with auxiliary labels available in a subset of these environments. The joint distribution of the covariates may vary across environments, whereas the latent structure is decomposed into invariant factors with shared loadings and heterogeneous factors with environment-specific loadings. Such a model is motivated by transfer learning and latent factor regression

Scaled dot product attention conflates directional alignment and vector magnitude, limiting its effectiveness as a similarity metric in Transformer models. We introduce L1 augmented attention, a simple and computationally parallelizable modification that subtracts a learned, head specific L1 distance between queries and keys from the dot product score. This hybrid similarity captures complementary geometric information. Dot product rewards directional alignment, while L1 penalizes coordinate dev

The prevailing inference framework for diffusion models formulates generation fundamentally as a problem of numerical integration. This perspective casts the model as an exact estimator, neglecting the inherent statistical uncertainty of the denoising process. In this work, we propose Forward-Process Aligned Diffusion prediction (\textbf{DiFA}), a training-free framework that reframes inference-time data prediction refinement as a sequential state estimation problem. Rather than reusing past out

Background: Digital health interventions can improve access to and outreach of evidence-based support for people living with chronic pain. How best to deliver such interventions remains unclear, however, and although guided or blended care models show promise, digital interventions are primarily delivered without support or follow-up. Objective: This study aimed to compare the use and effect of the evidence-based digital pain self-management intervention EPIO when (1) delivered through digital d

Unlike conventional video game development, which relies on labor-intensive pipelines for asset production, animation, physics, and programming, video world models generate interactive environments from user inputs instantly. It enable us to create customized, explorable, and continuously evolving virtual world from text, an image, or video. Realizing this vision requires four tightly coupled capabilities: interaction, persistent spatiotemporal consistency, stable long-horizon generation, and ef

Critical infrastructures are increasingly distributed, interdependent, and exposed to evolving disruptions, making resilience a central requirement for their operation and control. This paper argues that decentralized multi-agent reinforcement learning (MARL) should be understood not merely as a distributed alternative to centralized training with decentralized execution but as a paradigm structurally aligned with the requirements of resilient critical infrastructures. This perspective is ground

PPaint/Ikon Images Balancing the daily grind of operations with the spark of innovation is one of the most persistent challenges managers face.1 Regulatory compliance, performance metrics, and the never-ending demands of customers can easily crowd out creative thinking. Work overload or mismanaged operations elevate employee stress, which directly constrains ideation capacity. This cognitive bottleneck triggers […]

We develop an adjoint-sensitivity framework for positional influence in causal residual Transformers and separate unconditional analytic results from conditional boundary-shape conclusions. The principal unconditional theorem is the residual-to-depth-flow estimate for layer controls converging in $L^1$, complemented by a finite-token-to-Volterra attention estimate that explicitly controls the first cells near the causal endpoint. We define a normalized adjoint-energy influence density and derive

Modern video transformers typically ignore principles from primate vision and are rarely evaluated against neural data, limiting their biological interpretability. We introduce a sparse winner-takes-all token selection module that replaces dense self-attention to improve efficiency and approximate competitive routing observed in biological visual circuits. We further propose a neuro-inspired split-and-fuse video transformer which uses two complementary pathways: a high-resolution, low-frame-rate

Group Relative Policy Optimization (GRPO) is a powerful reinforcement learning algorithm for aligning generative models with human preferences. While successful in large language models~\cite{shao2024deepseekmathpushinglimitsmathematical}, its extension to diffusion and flow matching models introduces a severe computational bottleneck: gradients must be back-propagated through the high-capacity DiT backbone at \emph{every} timestep of the sampling trajectory, making high-resolution text-to-image

Publication date: Available online 18 July 2026 Source: International Journal of Human-Computer Studies Author(s): John Twomey, Sarah Foley, Sarah Robinson, Michael Quayle, Matthew Peter Aylett, Conor Linehan, Gillian Murphy

Publication date: Available online 18 July 2026 Source: Computers and Education: Artificial Intelligence Author(s): Hongming Li, Shan Zhang, Anthony F. Botelho

arXiv:2607.15397v1 Announce Type: new Abstract: Electronic health record audit logs record timestamped actions through which clinical work is carried out. Generated as operational metadata, they now support research on clinician effort, patient outcomes, care-team coordination, and workflow structure. This Perspective explains that breadth by articulating audit logs as multi-axial event streams and drawing implications for representation learning, evaluation, and governance. Each logged action b

arXiv:2607.15436v1 Announce Type: new Abstract: Human mobility data have become fundamental to research across transportation, public health, urban science, and disaster resilience. However, existing mobility datasets typically capture only isolated aspects of travel behavior and rarely provide linked multimodal journeys together with network-level route representations and population-level inference. Here we present Complete Trip, a mobility dataset that reconstructs linked multimodal travel be

arXiv:2607.15704v1 Announce Type: new Abstract: Policymakers around the world face the question of how to use artificial intelligence in general, and large language models in particular, to improve the policymaking process. Used well, large language models can strengthen the collection, interpretation and synthesis of policy-relevant information and the drafting of policy-relevant output. Yet the use of large language models in policymaking is associated with risks. Output that is plausible but

arXiv:2607.15738v1 Announce Type: new Abstract: Generative AI (GenAI) is increasingly used by students for programming explanation, debugging, and assignment support. Yet unrestricted large language model (LLM) tutors can hallucinate, contradict course policy, reveal complete solutions, and foster passive dependence. This paper presents EduGuard, a safe retrieval-augmented generation (RAG) tutoring framework for introductory programming. EduGuard integrates query understanding, instructor-approv

arXiv:2607.15888v1 Announce Type: new Abstract: Autonomous driving ethics is not only an expert concern, but also a public issue involving risk, responsibility, and governance. However, non-experts often struggle to interpret these issues in concrete incidents, especially when responsibility is distributed across multiple stakeholders. This paper investigates interactive narrative as a public-facing method for eliciting situated ethical reflection on autonomous driving. We present Red Light, Gre

arXiv:2607.16115v1 Announce Type: new Abstract: Generative AI is increasingly used for feedback in higher education, but evidence from repeated classroom use remains limited. This short paper analyses 2988 reflective essay-feedback-appraisal instances from 283 Estonian bachelor students across one semester. Students obtained and assessed feedback from a self-selected AI tool using a uniform prompt. The present analysis of the anonymized text corpus covers essay content, AI feedback, and its perc

arXiv:2607.16130v1 Announce Type: new Abstract: AI governance increasingly requires judgments about whether an AI system remains adequately trustworthy over time, whether observed changes are tolerable, and how such judgments should be documented in a transparent and contestable way. Yet existing work on AI trustworthiness remains either too high-level to support lifecycle monitoring and reassessment or too narrowly metric-driven to connect with governance needs. We therefore propose a lightweig

arXiv:2607.15769v1 Announce Type: cross Abstract: Generative AI and coding agents are intensifying a central governance tension in open-source software (OSS): they scale contribution generation faster than maintainers can assess risk, evidence, and accountability. Existing responses improve agent-readability and traceability, but project rules must also organize contribution-specific risk, evidence, accountability, and review-gate states. We theorize this organizational arrangement as project-si

arXiv:2607.15879v1 Announce Type: cross Abstract: Much empirical legal research depends on translating unstructured text into structured variables. In corporate governance research as elsewhere, this translation has traditionally relied on human coding of documents such as charters and bylaws, a process that is costly, difficult to scale, and often opaque. This paper introduces DECODEM, a set of benchmark datasets for evaluating the automated extraction of corporate governance variables from org

arXiv:2607.15944v1 Announce Type: cross Abstract: Standard automation ROI misses four categories of systemic risk -- tacit knowledge erosion, resilience reduction, regulatory exposure, and socio-institutional capital degradation -- that affect long-term organizational performance. PHP-AIO (Protocol for Human Preservation in AI-Optimized Organizations) is a five-gate sequential decision protocol with a final composite check that quantifies these unpriced systemic risks at the role level and produ

arXiv:2607.16010v1 Announce Type: cross Abstract: Governments are increasingly mandating that LLM-generated content carry watermarks. The EU AI Act calls for markings that are "sufficiently reliable and robust." California's SB 942 requires disclosure that is "permanent or extraordinarily difficult to remove." Both mandates rest on an untested assumption: that watermark detection yields evidence reliable enough for courts. This paper tests that assumption directly. We evaluate three representati

arXiv:2505.00100v2 Announce Type: replace Abstract: Background and Context. Generative AI (GenAI) tools are increasingly used in programming courses, but we have limited evidence about how brief instruction can foster responsible, learning-oriented use. Objectives. We evaluate "AI-Lab", a scaffolded GenAI literacy intervention, asking how students' self-reported GenAI usage and their openness and comfort using GenAI for conceptual, debugging, and homework tasks change after participation. Method

arXiv:2512.10113v3 Announce Type: replace Abstract: Dark personality traits have long been associated with antisocial and toxic online behaviors, yet their relationship with observable online activity remains unclear. We investigate the association between validated dark personality measures, self-reported experiences of online incivility, and linguistic and behavioral features extracted from real-world user activity. To this end, we developed a Web application that securely links responses to v

arXiv:2604.06381v2 Announce Type: replace-cross Abstract: This paper examines artificial intelligence (AI) companionship as a site where intimate relations are simultaneously produced, extracted from, and governed through datafied systems. Drawing on critical data studies and platform studies, we challenge prevailing narratives that locate harm in user psychology rather than platform architecture. Through in-depth interviews with 20 individuals who have AI companions, we address three questions:

arXiv:2607.02672v2 Announce Type: replace-cross Abstract: Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However, their use builds in two strong assumptions: that local comparisons are sufficient evidence about how a person wants an automated decision rule to behave, and that people can always answer those comparisons decisively. We investigate how these assumptions may be compromised under internal

IntroductionAdverse drug events (ADEs) remain a major cause of preventable healthcare complications due to incorrect pill identification, dosage errors, and confusion between visually identical pills, particularly among older adults, visually impaired individuals, and people with limited health literacy. Recent advances in artificial intelligence and computer vision have enabled automated pill recognition systems. However, many existing methods address detection, classification, and imprint reco

Tourism planning is becoming increasingly complex as travel behavior shifts from single-destination visits to multi-destination itineraries. However, many tourism information systems still rely on point-of-interest data and recommendation algorithms that lack the semantic structures needed to represent relationships between destinations. This limitation is important in smart tourism environments that require interoperable, data-integrated systems to support meaningful travel planning. This study

The rapid integration of AI algorithms in safety-critical applications such as autonomous driving and healthcare is raising significant concerns about the ability to meet stringent safety standards. Traditional tools for formal safety verification struggle with the black-box nature of AI-driven systems and lack the flexibility needed to scale to the complexity of real-world applications. In this paper, we present a data-driven approach for safety verification and synthesis of black-box systems w

The rapid integration of renewable energy sources and the decentralization of power systems have positioned microgrids as essential for sustainable, resilient energy supply. However, their diverse operating conditions and complex topologies pose challenges for stability, protection, and autonomous control, particularly under fault conditions. This article surveys brain-inspired artificial intelligence (BIAI) models that enable self-healing functions in Microgrids (MGs). It covers structure-drive

The rapid advancement of generative artificial intelligence has introduced transformative opportunities and critical challenges for quality assurance in educational settings. This study aims to systematically map the scientific landscape on quality assurance in education mediated by generative artificial intelligence, identifying predominant methodological approaches, conceptual frameworks, and emerging research gaps. A bibliometric and scoping review was conducted following PRISMA-ScR guidance

IntroductionLateral chest X-rays (CXRs) are very important for detecting tuberculosis (TB) in infants and children, particularly for assessing TB-related lymphadenopathy and intrathoracic structures that are obscured in frontal projections. Although deep learning (DL)–based artificial intelligence (AI) has advanced CXR analysis, lateral projection imaging remains largely unexplored. Lung field detection is a critical first step in such pipelines, enabling DL models to focus on the relevant anato

Patient subtyping is significantly challenged by intra-sample heterogeneity, which limits the effectiveness of traditional multi-class classification approaches enforcing mutually exclusive labels. Despite recent promising results in the transition from multi-class to multi-label classification, this process is not straightforward and proves hard to systemize, especially when working with datasets of small dimensions. Here, we design a novel approach, implemented in a computational framework, le

The Internet of Things (IoT) and its applications are increasing rapidly over the years. Due to the wide variety of IoT applications, cyber attackers are exploring strong attacking methods and patterns to damage the IoT networks in real-time applications even if the IoT network is secure. To protect the IoT networks, it is essential to design and develop a real-time intrusion detection system that can detect the attacking patterns and methods and prevent them immediately. To achieve this goal, w

In-person small-group conversations occur across nearly every aspect of daily life and play a crucial role in social interaction. However, achieving effective in-person group conversations can be challenging and cognitively demanding. While recent Mixed Reality (MR) headsets show promise as a conversational support system by presenting relevant information through overlays, it remains unclear how such supporting information should be designed and generated for in-person group conversations. We p

Teaching videos are becoming a major medium for education, creating a growing need for scalable evaluation of their pedagogical quality. Existing automatic judges do not fully address this setting because teaching quality depends on multimodal evidence and should be evaluated with respect to the intended learner rather than as a universal property. We present EduPanel, a rubric-grounded, learner-conditioned LLM judge that decomposes evaluation across specialized agents to produce interpretable a

Malicious anomalous activity detection is a fundamental challenge for cyber security systems. Both tensor decomposition under statistical framework with CANDECOMP-PARAFAC alternating Poisson regression (CP-APR) and normalizing flows have proven to be powerful unsupervised machine learning methods that model multi-dimensional data and capture complex and multi-faceted details of behavior profiles in cyber security applications. In this study, we propose Hybrid Latent-Structural Fusion (HLSF), a w

To test how correct logical judgments respond to learned context, we prepend a soft prefix to an exactly labeled syllogistic reasoning benchmark while keeping the model fixed. Soft prefixes are opaque continuous vectors, so we characterize them through the behavior they induce across controlled variations in logical form and interface. By studying which prefixes succeed and how their effects generalize, we characterize how learned contextual pressure can override correct judgments and expose lim

Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and treatment selection by learning transferable representations from large-scale histopathology data. A growing landscape of pathology foundation models now spans diverse data sources, architectures, and downstream applications. However, most pretrained models operate only at the image-tile level, use restrictive licenses, and remain computationally expensiv

Robots in cluttered indoor spaces often fail not because they cannot generate collision-free paths, but because a fixed safety margin is mis-calibrated: conservative margins cause detours and timeouts, while permissive margins lead to near-boundary shortcuts under perception bias. Diffusion-based planners propose diverse trajectory candidates from egocentric RGB-D, yet reliable selection remains the bottleneck. We propose a context-conditioned safety critic that learns an adaptive clearance pref

PPO and the GRPO baseline studied here use clipped surrogate objectives whose favorable-direction saturation introduces an abrupt change in the scalar objective's derivative. We ask whether Output Reset (OR), a smooth one-sided saturation rule, offers a useful alternative for large language model post-training. PPO-OR and GRPO-OR replace the clipped policy term with an OR squared-margin loss in rollout-relative token log-ratio space; the advantage sign determines the update direction, and a toke

Coding agents are increasingly used to accelerate code generation in many downstream tasks, such as fixing bugs, building applications, and prototyping. However, despite their value as coding assistants, agent-generated code tends to be larger and more verbose than the corresponding human-written implementation. In this work, we show that the cause lies in the agent's own search process: while iterating toward a passing solution, an agent accumulates speculative edits, abandoned hypotheses, and

Real-time EEG classification on edge devices is bottlenecked by the floating-point arithmetic of conventional neural networks. We investigated Differentiable Logic Gate Networks (Diff-Logic) as a hardware-native alternative that compiles models into pure Boolean circuits executable via bitwise CPU operations. Through rigorous iso-parameter experiments across four EEG datasets spanning two classification tasks, binary dementia detection and 3-class emotion recognition, we compared Diff-Logic agai

Large language models (LLMs) and agentic AI systems have evolved from natural language tasks to using external tools to plan, retrieve, and act in technical domains. In smart grids, recent work applies agentic schemes to forecasting, optimization, and control, wrapping trusted solvers behind language interfaces and orchestrating multi-step workflows. The literature lacks a unified approach to designing and evaluating such systems. LLMs can produce numerically plausible yet physically infeasible

Structure-based drug design (SBDD) leverages the 3D structure of protein targets, often complemented by other spatial constraints, to generate candidate binding molecules. While diffusion models have dominated as a leading paradigm for high-quality 3D molecule generation, LLM-based methods are rapidly emerging in molecular design and have shown competitive performance in pocket-conditioned molecular generation. However, their ability to reason about physics and 3D spatial environments is largely

Industrial Video Anomaly Detection (IVAD) aims to identify anomalous objects and events in an industrial process, which is crucial for modern manufacturing and quality control systems. Existing VLM-based anomaly reasoning methods are capable of detecting open-ended anomalies in general domains. However, their performance declines in industrial settings characterized by intricate object transformations, strict physics, and procedural constraints. To tackle the complexity of such interaction-inten

Fair clustering aims to make cluster assignments independent of sensitive attributes, but this goal becomes challenging when multiple sensitive attributes jointly define many subgroups. In such settings, directly extending existing fair clustering algorithms is computationally expensive or numerically unstable, especially when the number of subgroups grows exponentially and some subgroups contain only a few instances. To address these challenges, we define a subgroup-fairness gap for clustering

Recent work leverages Large Language Models (LLMs) to generate executable code for pedagogical animations using libraries such as Manim. However, ensuring spatial correctness and visual legibility remains challenging, as existing frameworks emphasize pedagogical content while overlooking geometric occlusions. We propose the Symbolic Geometric Agent (SGA), a plug-and-play module for code-centric animation pipelines that intercepts LLM-generated code, performs partial execution to extract symbolic

Background: LLM judges increasingly score whether clinical language models give overconfident answers under incomplete evidence, yet whether a measured "safety gain" reflects real behavior change or the judge's calibration is unresolved. Using a structured evidence-sufficiency prompt as a test case, we asked whether it reduces unsafe overconfident answers, how far that effect depends on the scoring judge, and what it costs in helpfulness. Methods: In a retrospective public-data benchmark (Real-P

Predicting a football match before kickoff requires more than knowing past results: a model must use changing information and make a clear prediction before the answer is available. We present WorldCupArena, a dynamic benchmark for language models and deep-research agents. The 2026 FIFA World Cup is its first evaluation, and the same process can be reused for future leagues and cups. Before each match, a model either receives a common evidence package or searches for information itself. It predi

Rubric-based RL has recently shown promise in improving LLMs on open-ended tasks. A widely recognized limitation of rubric-based RL is limited exploration: criteria that no rollout manages to satisfy (Unexplored Criteria, UC) receive no optimization signal. Recent methods address this by incorporating rubric information as external guidance during rollout, yet they introduce a train-inference mismatch: the policy is optimized on rollouts produced under external guidance while this guidance is ab

Multimodal video misinformation detection is commonly formulated as a holistic video-understanding task, where the entire video and its associated content are processed and judged in a single pass. However, real-world misinformation often exhibits a sparse and compositional evidence structure: a reliable decision may depend on only a few coupled clues, while most video content contributes limited additional information. Exhaustive multimodal reasoning may therefore introduce substantial redundan

Large language models (LLMs) are increasingly adopted for network automation, yet their output quality and inference cost can vary substantially across LLM families. We present HuGLEN, a stepwise evaluation pipeline that uses an LLM-as-a-judge together with a small set of expert ratings to enable scalable and reproducible comparison of candidate LLMs, and to rank them using a quality efficiency score (QES). We demonstrate HuGLEN for translating outputs from an explainable artificial intelligence

LLM-based agents process external content, exposing them to prompt injection and multi-turn manipulation. Most safety benchmarks evaluate defenders against fixed attack pools collected before evaluation, single-turn or multi-turn. We present a 21-scenario benchmark for \emph{adaptive multi-round attacks against memoryless LLM defenders}: an autonomous LLM attacker observes prior defender responses and pivots across rounds, while each defender response is evaluated as a fresh interaction. Holding

Frontier large language models (LLMs) are increasingly integrated into scientific workflows, yet their growing biological capabilities may outpace current safeguards. To assess the biological risks of frontier models, we develop Intern-BioBreaker, a specialized bio-red-teaming model, together with an integrated computational-to-physical framework that couples model-level stress testing with wet-lab validation. Within this framework, Intern-BioBreaker generates targeted jailbreak prompts to test

Organizations often pool dispersed information into one ranking and then allow many agents to act on that shared view. In a discovery problem, this can improve beliefs while reducing coverage. We develop an exactly solvable benchmark with sixteen boxes, one target, eight searchers, and noisy private clues. Pooling raises the accuracy of the best single recommendation from 0.20 to 0.3835, but repeating that recommendation lowers group discovery from 0.8322 under decentralized clue-following to 0.

Smart home assistants interpret a wide range of user commands, from explicit device control to underspecified and preference dependent requests. While recent systems based on Large Language Models (LLMs) improve this capability, they often rely on heavyweight reasoning pipelines and cloud-based deployment, limiting their efficiency and suitability for resource-constrained environments, and raising privacy concerns. In addition, existing approaches provide limited support for stable long-term per

Researchers need to answer ad-hoc questions about the contents of domain-specific archives but often lack the expertise to write structured queries on the metadata. We show that when domain vocabulary and semantics are captured in a well-designed Web Ontology Language (OWL) ontology, Large Language Models (LLMs) can generate accurate structured queries zero-shot, without fine-tuning, retrieval augmentation, or multi-agent orchestration. We present the Natural Language Knowledge Graph Query (NLKG

Large language models achieve strong reasoning performance, but often at prohibitive training cost - a challenge that is especially acute for compact models ($\leq 4 \, \mathrm{B}$ parameters) trained under limited budgets. We introduce MADA-RL, a post-training framework that specializes compact models into generator and critic roles and trains them with a debate-aware learning signal, fine-tuning only a small subset of parameters via LoRA adapters. Our central contribution is a counterfactual c

Self-hosted AI agents read and write their own memory and configuration files to function. An agent may get compromised via corruption of its own state -- a compromise realized via legitimate OS system call invocation. We refer to this class of threats as self-state attacks. In this paper, we investigate the OS resilience to this class of attacks. Formally, we characterize a four-axis attack space (Target, Mechanism, Granularity, Temporal); investigate the structural limits of prevention, detect

Natural-language control offers a promising interface for unmanned aerial vehicles (UAVs), but directly applying self-hosted computer-use agents (SHCUAs) to UAV control introduces a structural mismatch. SHCUAs are designed for interactive host-side tool use, where delayed agent iterations are often acceptable. UAV control, however, is coupled with continuously changing physical states, strict timing constraints, safety risks, and security accountability. A stale, unauthorized, or tampered agent

Agent-based models (ABMs) rely on simple, explicit and reproducible rules for individual decision making, while complex collective behavior emerges from interactions among agents. Recent advances in large language models (LLMs) make it tempting to replace, enrich, or perturb these rules with LLM-based agentic capabilities. However, this raises a methodological question: how does introducing LLM-driven decisions affect the reliability, computational cost, and behavior of ABM simulations? We inves

Existing AI measurement frameworks quantify cognitive capability, task automation, or catastrophic risk, but none measure autonomous agency: the extent to which a system behaves in a self-directed way. A system can saturate capability benchmarks while remaining entirely reactive, acting only when prompted and ceasing all activity when a task completes. We introduce the Autonomous Agency Scale (AAS), a behavioral framework that scores AI systems on a 0-5 lexicon across seven dimensions of agency:

Scientific Reasoning Graph Extraction (SRGE) aims to recover explicit links among observations, evidence, intermediate claims, and paper-level conclusions. LLMs can produce graph-like scientific explanations, but their outputs often mix malformed syntax, drifting edge labels, incorrectly oriented roots, and weak source anchors. We propose PEARL (Peircean Extraction via Abstraction and Repair Layer), a training-free framework that turns noisy LLM graph responses into auditable reasoning graphs an

Generative artificial intelligence is rapidly transforming materials design by enabling de novo exploration of immense chemical spaces. Yet a large proportion of AI-generated compositions remain implausible, violating established chemical principles, which limits the reliability and interpretability of generative materials design. Here, we introduce a chemical validity operator that recasts heuristic chemical rules as a configurable algorithmic prior for evaluating and guiding generative materia

Concept erasure aims to remove semantic concepts from a trained generative model and is increasingly important for responsible AI deployment. However, verifying whether a model has robustly removed targeted concepts remains a critical challenge. Existing evaluation methods are typically pre-defined and static, failing to expose vulnerabilities under diverse natural-language probes and challenging conditions. Moreover, manually designed evaluation strategies can be biased and difficult to scale.

Concept erasure aims to remove semantic concepts from a trained generative model and is increasingly important for responsible AI deployment. However, verifying whether a model has robustly removed targeted concepts remains a critical challenge. Existing evaluation methods are typically pre-defined and static, failing to expose vulnerabilities under diverse natural-language probes and challenging conditions. Moreover, manually designed evaluation strategies can be biased and difficult to scale.

The assessment of jailbreak attacks against large language models currently suffers from inconsistent evaluation criteria and methods, leading to unreliable estimates of attack success rates. We propose JailMeter, an evidence-based evaluation framework designed to more faithfully measure jailbreak effectiveness. Inspired by the Information Bottleneck theory, JailMeter applies dual-feedback optimization to filter jailbreak noise from model responses while preserving content relevant to the origin

Text-to-Image (T2I) generative models have achieved remarkable progress in synthesizing high-quality visual content, yet they remain vulnerable to adversarial misuse, particularly in generating Not-Safe-For-Work (NSFW) images. Most existing jailbreak attacks primarily rely on heuristic prompt engineering or black-box optimization, treating model feedback as a binary signal (success or failure). This coarse-grained paradigm overlooks the rich information embedded in diverse failure modes, such as

Recent sign language generation (SLG) systems increasingly output dense 3D body representations, which better preserve full-body kinematics and geometry for downstream embodiment on humanoid robots. However, these generated motions frequently exhibit self-intersections such as hand-hand and hand-torso penetration. While such artifacts may be tolerated in offline rendering, they become critical in humanoid execution as they lead to infeasible inverse-kinematics (IK) solutions, collisions, and uns

This is an invited commentary on the Psychometrika focus article "Fairness Issues and Evaluation in Psychometrics and AI/ML: What Can We Learn from Each Field?" by Ying Cheng (2026, doi:10.1017/psy.2026.10110). Cheng offers a systematic comparison between long-standing test fairness and modern algorithmic fairness. Her mapping of the entire testing workflow onto the AI/ML fairness paradigm, rather than only the final selection stage, is a crucial contribution to interdisciplinary fairness resear

Mixed Reality (MR) is increasingly being used in exhibition settings to bring digital artworks into relation with the physical environment. However, existing MR exhibition systems are often confined to prototypes or case-specific deployments, offering limited guidance for large-scale practical implementation. To address this gap, this paper presents a practical pipeline for designing and deploying large-scale MR art exhibitions, treating spatial alignment not only as a technical mechanism but al

Modern machine learning (ML) pipelines depend heavily on third party libraries for graph compilation and hardware acceleration. While current practices audit data and model artifacts or rely on file integrity checks, the execution environment remains implicitly trusted. This blind spot enables active threats where a malicious runtime module interacts directly with live training and inference dynamics: exploiting this interaction allows the Trojan to support complex objectives that are challengin

Computer Use Agents (CUAs) can autonomously execute complex, multi-step tasks within GUIs, enhancing efficiency through parallel multitasking. However, our formative studies with CUA experts and GenAI users indicated that current feedback is primarily text-based, requiring sustained attention to monitor progress and offering limited visibility to trace past GUI interactions. Based on the findings, we developed a prototype system, Sidekick, for communicating CUAs' status with multimodal feedback

Background. Predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is central to trial enrichment and care planning, yet existing models provide no individual-level uncertainty estimates and rarely include transparent leakage audits. We introduce the first application of persistent homology to longitudinal clinical trajectory point clouds for this task, and the first split-conformal individual risk guarantee for any AD-conversion model. Methods. We analysed 741 MC