AI ethics evidence index Search
Source-linked daily record
Evidence record 57 · automatically gathered

SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification

Cybersecurity systems must adapt rapidly to emerging threats. However, labeled data for new threat categories is unavailable when those threats first appear. Generalized zero-shot learning offers a natural solution by enabling recognition of unseen classes through auxiliary semantic knowledge rather than labeled examples. Large language models are particularly promising in this setting because they can convert unstructured CTI reports into semantic prototypes for emerging threats. However, apply

Record details

Published: 10 July 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Also mentions Meta · Shared topic: Safety & alignment

A systematic review of toxicity in large language models: definitions, datasets, detectors, detoxification methods and challenges

Artificial Intelligence Review · 2 July 2026

Also mentions Meta · Shared topic: Safety & alignment

Meta-Transfer Learning for mmWave Beam Alignment

arXiv · 1 July 2026

Also mentions Meta · Shared topic: Safety & alignment

Meta-Learned Reward Shaping for Reinforcement Learning from Human Feedback

arXiv cs.LG · 28 July 2026

Also mentions Meta · Shared topic: Safety & alignment

Constructing Executable Analytical Knowledge Representations for Meta-Analysis Synthesis Using an Agentic Harness

arXiv · 3 August 2026

Also mentions Meta · Shared topic: Safety & alignment

AMR-SD: Asymmetric Meta-Reflective Self-Distillation for Token-Level Credit Assignment

arXiv · 18 May 2026

Also mentions Meta · Shared topic: Safety & alignment

Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment

arXiv · 27 April 2026

How to cite this record

ethics.ai (10 July 2026), “SMETA-ZSL:Semantic Meta-Alignment for Zero-Shot Threat Classification,” evidence record 57, https://ethics.ai/record/57 (originally published by arXiv).

JSON

Use and limitations

This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.