Branch2Skill: Efficient Skill Evolution Through Reasoning Trees
Yanwei Ren, Haotian Zhang, Likang Xiao, Jiaxing Huang, Jiayan Qiu, Baosheng Yu, Quan Chen, Liu Liu
cs.AI
Submitted: 2026-08-09
Updated: 2026-08-11
Comments: 9 pages, 6 figures, 3 tables. Technical report
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- EvoSkill: Automated Skill Discovery for Multi-Agent Systems
- SkillCAT: Contrastive, Assessment-Augmented and Topology-AwareSkill Self-Evolution for LLM Agents
- SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine
- Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models
- Branching Policy Optimization: Sandbox-Native Language Agent Reinforcement Learning
- LiveMathematicianBench: A Live Benchmark for Research-Level Mathematical Reasoning with Proof Sketches
- OpenClaw-Skill: Collective Skill Tree Search for Agentic Large Language Models
- SkillGen: Verified Inference-Time Agent Skill Synthesis
- Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
- OfficeQA Pro: An Enterprise Benchmark for End-to-End Grounded Reasoning
- SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe
- ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
- Voyager: An Open-Ended Embodied Agent with Large Language Models
- SkillGrad: Optimizing Agent Skills Like Gradient Descent
- SkillOpt: Executive Strategy for Self-Evolving Agent Skills
- SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories
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