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Evidence record 401 · automatically gathered

FLARE-AI: Flaw Reporting for AI

Flaw reporting for deployed AI systems is fundamental to identifying system failures and improving AI safety. Yet the AI reporting ecosystem is fragmented: researchers who identify flaws often do not know what or where to report, and groups who receive reports rarely share them with other relevant stakeholders. As a result, good-faith reporters duplicate effort by submitting many different forms, and recipients lack standardized, triage-ready information. We audit 12 reporting systems published

Record details

Published: 30 June 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Transparency
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.

Shared topic: Safety & alignment · Shared topic: Transparency

FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning

arXiv · 30 June 2026

Shared topic: Safety & alignment · Shared topic: Transparency

EvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety Failures

arXiv · 29 June 2026

Shared topic: Safety & alignment · Shared topic: Transparency

Explainable Reinforcement Learning for Adaptive Traffic Signal Control

arXiv · 4 July 2026

Shared topic: Safety & alignment · Shared topic: Transparency

Bridging Vision and Language Concepts through Optimal Transport Semantic Flow

arXiv · 25 June 2026

Shared topic: Safety & alignment · Shared topic: Transparency

NebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research

arXiv · 25 June 2026

Shared topic: Safety & alignment · Shared topic: Transparency

The interpretability paradox in cancer imaging and risk prediction: a critical narrative review of explainable AI, failure modes, and design alternatives

Artificial Intelligence Review · 7 July 2026

How to cite this record

ethics.ai (30 June 2026), “FLARE-AI: Flaw Reporting for AI,” evidence record 401, https://ethics.ai/record/401 (originally published by arXiv).

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