AI RESEARCH
Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents
arXiv CS.AI
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ArXi:2604.15877v1 Announce Type: new As LLM agents scale to long-horizon, multi-session deployments, efficiently managing accumulated experience becomes a critical bottleneck. Agent memory systems and agent skill discovery both address this challenge -- extracting reusable knowledge from interaction traces -- yet a citation analysis of 1,136 references across 22 primary papers reveals a cross-community citation rate below 1