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VLMs are prone to critical failures that vary significantly across cultures, exposing the inadequacy of Western-centric safety benchmarks.
Compact models can achieve frontier reasoning performance with minimal latency overhead, thanks to a novel method that distills explicit reasoning patterns into structured prompts.
LLMs still struggle with infrequently occurring knowledge, and this paper provides a structured framework to understand why, how we can fix it, and what the implications are for responsible AI.