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Presents SkillTrace, a multi-trace provenance auditing framework for LLM-agent skill reuse that extracts expression, implementation, and operational traces, achieving strong accuracy on a benchmark and enabling large-scale wild audits.
Continual Harness is a reset-free, self-improving agentic harness that achieves 20.54% on ARC-AGI-3 at a cost of $774 by storing memories, reusing skills, and refining its prompt, outperforming prior baselines like Hermes and OpenClaw with greater efficiency.
This paper introduces SkillMigrator, an LLM web agent that learns reusable skills and transfers them across websites by matching layout structure rather than domain-specific metadata, reducing LLM action count by 8-10% on WebArena and Mind2Web benchmarks.
ExpGraph is a model-agnostic framework that enables LLM agents to reuse past experiences via a self-evolving graph of skills and failures, improving task performance by 12–21% without retraining the executor.
This paper introduces SkillLens, a hierarchical framework for adaptive multi-granularity skill reuse in LLM agents, demonstrating improved accuracy and cost-efficiency on benchmark tasks.