AINeutralarXiv – CS AI · 14h ago7/10
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When Should Models Change Their Minds? Contextual Belief Management in Large Language Models
Researchers introduce BeliefTrack, a benchmark for evaluating how large language models manage contextual information over long interactions—deciding when to update beliefs, preserve state, or ignore noise. The study reveals vanilla LLMs fail significantly at this task, while reinforcement learning with belief-state rewards reduces failures by 71% on average.