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SkillZip is a new method for compressing the accumulated skills of self-evolving agents without evaluation rollouts, by finding a minimal faithful structural explanation that reuses repeated rules and procedures while preserving rare exceptions.
SKIM is an adaptive multi-resolution soft token compression framework that compresses procedural skills for LLMs, maintaining task performance while reducing prefill cost and latency.