Graph world-model rollout error splits into a spectral topology factor and a model-norm factor, and Error-Aware training improves long-horizon stability when structure is fixed or evolving.
Audited skill-graph self-improvement for agentic llms via verifiable rewards, experience synthesis, and continual memory
4 Pith papers cite this work. Polarity classification is still indexing.
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citation-polarity summary
years
2026 4roles
background 2polarities
background 2representative citing papers
Catalogs ten patterns and synthesizes a four-layer reference architecture for skill harnessing in LLM agents, evaluated via cross-instantiation on eight systems.
SkillGraph jointly evolves agent skills and collaboration topologies in multi-agent vision-language systems using a multimodal graph transformer and a skill designer, yielding consistent performance gains on benchmarks.
A survey that defines agent skills as reusable procedural artifacts and reviews methods, resources, and applications across their representation, acquisition, retrieval, and evolution stages.
citing papers explorer
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Understanding Rollout Error in Graph World Models
Graph world-model rollout error splits into a spectral topology factor and a model-norm factor, and Error-Aware training improves long-horizon stability when structure is fixed or evolving.
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Harnessing Agent Skills: Architectural Patterns and a Reference Architecture for Skill-Mediated LLM Agents
Catalogs ten patterns and synthesizes a four-layer reference architecture for skill harnessing in LLM agents, evaluated via cross-instantiation on eight systems.
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SkillGraph: Self-Evolving Multi-Agent Collaboration with Multimodal Graph Topology
SkillGraph jointly evolves agent skills and collaboration topologies in multi-agent vision-language systems using a multimodal graph transformer and a skill designer, yielding consistent performance gains on benchmarks.
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A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications
A survey that defines agent skills as reusable procedural artifacts and reviews methods, resources, and applications across their representation, acquisition, retrieval, and evolution stages.