#skill-transfer News & Analysis

3 articles tagged with #skill-transfer. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · Jun 237/10

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Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluation

Researchers introduce AFTER, a benchmark evaluating how procedural memory in large language models transfers across tasks, roles, and model types. Testing on 382 enterprise tasks across six professional roles, the study finds that procedural memory improves performance by 3.7-6.7 points per refinement round, with multi-model trained skills achieving 73.1% cross-model accuracy—though some skills generalize broadly while others become role-specific.

AIBullisharXiv – CS AI · Mar 67/10

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SkillNet: Create, Evaluate, and Connect AI Skills

Researchers introduce SkillNet, an open infrastructure for creating, evaluating, and organizing AI skills at scale to address the problem of AI agents repeatedly rediscovering solutions. The system includes over 200,000 skills and demonstrates 40% improvement in agent performance while reducing execution steps by 30% across multiple testing environments.

AINeutralarXiv – CS AI · Jun 96/10

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Continual Quadruped Robots Coordination via Semantic Skill Discovery

Researchers present Conquer, a semantic skill-library framework enabling multi-quadruped robots to learn new coordination tasks sequentially without forgetting previously acquired skills. The system uses a variable-cardinality architecture and semantic descriptors to retrieve and adapt existing skills for new tasks, achieving 95.6% success rates in simulation and real-world validation on Unitree Go2 robots.