arxiv
PublishedOctober 21, 2026 at 4:00 AM
HABIT-Bench: Evaluating Habit Induction from Longitudinal Weak Evidence in Agent Memory
Publisher summary· verbatim
arXiv:2610.24520v2 Announce Type: replace Abstract: In long-term interactions with large language model (LLM) agents, users reveal habits through their choices and actions. These habits capture implicit user information that agents must infer across conversations. However, individual observations ma
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response10harxivLearning Transferable Latent User Preferences for Human-Aligned Decision Making10harxivRepair the Core, Not the Symptom: Planning-Graph Repair for Long-Horizon Agents10harxivIndustryForge-27B: A Domain-Enhanced Multimodal Foundation Model for Industrial CAD10hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗