AI RESEARCH
MemBuilder: Reinforcing LLMs for Long-Term Memory Construction via Attributed Dense Rewards
arXiv CS.CL
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ArXi:2601.05488v3 Announce Type: replace Maintaining consistency in long-term dialogues remains a fundamental challenge for LLMs, as standard retrieval mechanisms often fail to capture the temporal evolution of historical states. While memory-augmented frameworks offer a structured alternative, current systems rely on static prompting of closed-source models or suffer from ineffective