AI RESEARCH
ContextWeaver: Selective and Dependency-Structured Memory Construction for LLM Agents
arXiv CS.CL
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ArXi:2604.23069v1 Announce Type: new Large language model (LLM) agents often struggle in long-context interactions. As the agent accumulates interaction history, context management approaches such as sliding window and prompt compression may omit earlier structured information that later steps rely on. Recent retrieval-based memory systems surface relevant content but still overlook the causal and logical structure needed for multi-step reasoning. We