#training-free-learning News & Analysis

2 articles tagged with #training-free-learning. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Jun 96/10

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ConMem: Structured Memory-Guided Adaptation in Training-Free Multi-Agent Systems

ConMem introduces a training-free framework for multi-agent systems that uses structured memory cards and relation-aware graphs to improve adaptation without additional training. The approach reduces inference overhead by over 80% and prunes more than 50% of candidate expansions while maintaining performance across multiple benchmarks.

AINeutralarXiv – CS AI · Jun 26/10

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SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories

SkillAdaptor introduces a training-free framework for refining external skills used by LLM agents, using step-level failure attribution instead of trajectory-level feedback. The method demonstrates consistent improvements across three evaluation benchmarks (WebShop, PinchBench, Claw-Eval) with gains up to 1.8 points, offering more stable and auditable skill maintenance for autonomous agent systems.

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