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Matching papers

HABIT-Bench: Evaluating Habit Induction from Longitudinal Weak Evidence in Agent Memory

84 upvotes · 20 OCT 2026 · Junming Zhang, Rubin Wei, Xu Cheng et al.

This paper evaluates how well large language model agents can infer and apply habits from incomplete or weak evidence, and how this relates to their performance in real-world conversations. Practitioners caring about conversational AI might care about this research because it can help improve agents' ability to understand user behavior and adapt to changing habits.

agent memoryhabit inductioncontinual learningnatural language processingdialogue systems