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Hazard or Anomaly? Evaluating VLMs for Understanding Dangers and Discrepancies
BACKGROUND
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23 Jul
Hazard or Anomaly? Evaluating VLMs for Understanding Dangers and Discrepancies
REPORT · WHAT · ArXiv CS.AI
Other feeds and industry voices
9 May
Understanding Annotator Safety Policy with Interpretability
arXiv:2605.05329v1 Announce Type: new Abstract: Safety policies define what constitutes safe and unsafe AI outputs, guiding data annotation and model development. However,
REPORT · WHAT · ArXiv CS.AIOPEN STORY
13 Aug
Glance, Scrutinize, and Think: Advancing Video Anomaly Detection from Training-Free to Agentic Reasoning
arXiv:2608.11260v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) aims to identify anomalous events and localize their temporal intervals. Existing approaches exhibit
REPORT · WHEN · ArXiv CS.AIOPEN STORY
25 Mar
Between Rules and Reality: On the Context Sensitivity of LLM Moral Judgment
arXiv:2603.23114v1 Announce Type: new Abstract: A human's moral decision depends heavily on the context. Yet research on LLM morality has largely studied fixed scenarios. We
REPORT · WHAT · ArXiv CS.AIOPEN STORY
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