#over-refusal News & Analysis

2 articles tagged with #over-refusal. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Mar 57/10

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Discern Truth from Falsehood: Reducing Over-Refusal via Contrastive Refinement

Researchers introduce DCR (Discernment via Contrastive Refinement), a new method to reduce over-refusal in safety-aligned large language models. The approach helps LLMs better distinguish between genuinely toxic and seemingly toxic prompts, maintaining safety while improving helpfulness without degrading general capabilities.

AINeutralarXiv – CS AI · Jun 236/10

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AOR-Bench: Do Large Audio Language Models Over-Refuse Pseudo-Harmful Queries?

Researchers introduce AOR-Bench, the first benchmark measuring over-refusal in Large Audio Language Models (LALMs), where safety mechanisms incorrectly reject benign queries. Testing 12 models across six families reveals widespread over-refusal, particularly when audio context could disambiguate potentially harmful speech, prompting exploration of mitigation strategies like Chain-of-Thought reasoning.