Tagged articles

skill evolution

7 articles · Page 1 of 1

Jul 23, 2026 · Artificial Intelligence

Teaching Agents to Evolve: The Hierarchical Skill Meta‑Evolving Framework HiSME

HiSME, a lightweight hierarchical skill meta‑evolution framework from Tsinghua and Huawei, enables LLM agents to accumulate execution experience without updating model parameters by evolving both task‑specific skills and the meta‑skills that generate and maintain them, improving performance on multi‑turn tool use and open‑world tasks.

HiSMELLM agentshierarchical framework

0 likes · 11 min read

Teaching Agents to Evolve: The Hierarchical Skill Meta‑Evolving Framework HiSME

PaperAgent

Jul 8, 2026 · Artificial Intelligence

Why Agent Skills Need Self‑Evolution: A Survey of 19 Frameworks and 10 Benchmarks

This survey from Rutgers and UNC Charlotte systematically reviews 19 agent‑skill evolution methods and 10 evaluation benchmarks, revealing critical gaps such as the lack of longitudinal tracking, binary pass/fail metrics, and one‑time security checks, and highlighting how separating diagnosis from rewrite improves cross‑task performance.

AgentEvaluationReinforcement Learning

0 likes · 9 min read

Why Agent Skills Need Self‑Evolution: A Survey of 19 Frameworks and 10 Benchmarks

Linyb Geek Road

Jun 29, 2026 · Artificial Intelligence

Understanding Loop Engineering: Concepts, Insights, and Practical Applications

The article explains Loop Engineering by distinguishing it from basic Agent Loops, outlines its six core components, showcases a text‑classification example, and discusses when the approach boosts efficiency versus when traditional Human‑in‑the‑Loop remains preferable.

AI agentsAgent LoopLoop Engineering

0 likes · 21 min read

Understanding Loop Engineering: Concepts, Insights, and Practical Applications

PaperAgent

May 16, 2026 · Artificial Intelligence

A First Systematic Survey of Agent Skills: Taxonomy, Techniques, and Applications

This survey analyzes the emerging field of Agent Skills, defining a formal skill model, categorizing acquisition pathways, detailing retrieval strategies, and outlining a five‑stage evolution process, while highlighting large‑scale skill repositories and their implications for AI product design.

AI agentsAgent SkillsSkill Retrieval

0 likes · 9 min read

A First Systematic Survey of Agent Skills: Taxonomy, Techniques, and Applications

PaperAgent

Apr 22, 2026 · Artificial Intelligence

How SkillClaw Enables Collective Evolution of Agent Skills in Real-World Use

SkillClaw introduces a centralized evolution framework that transforms user interactions into structured evidence, allowing LLM agents to refine, create, or skip skills based on aggregated success and failure patterns, with nightly validation ensuring only proven improvements are deployed, resulting in consistent performance gains across diverse tasks.

AI WorkflowLLM agentsbenchmark

0 likes · 13 min read

How SkillClaw Enables Collective Evolution of Agent Skills in Real-World Use

Machine Heart

Apr 14, 2026 · Artificial Intelligence

EverOS Global Beta Unveils Self‑Evolving Memory Layer for AI Agents

EverOS launches a global beta of its next‑generation memory infrastructure that lets autonomous agents automatically extract experience, cluster it semantically, and evolve reusable skills, boosting OpenClaw task success rates by up to 234.8% while addressing context‑window limits, multimodal retrieval, and developer transparency.

AI memoryEverOSEvoAgentBench

0 likes · 21 min read

EverOS Global Beta Unveils Self‑Evolving Memory Layer for AI Agents

SuanNi

Apr 2, 2026 · Artificial Intelligence

EvoSkill: Turning AI Failures into 12% Accuracy Gains with Automated Skill Evolution

The EvoSkill framework introduced by Sentient and Virginia Tech researchers equips large language models with a text‑feedback loop that automatically discovers, refines, and validates reusable agent Skills, boosting task‑specific accuracy by 12.1% and enabling cross‑domain transfer without altering the underlying model parameters.

AIAutomated LearningEvolutionary Algorithms

0 likes · 11 min read

EvoSkill: Turning AI Failures into 12% Accuracy Gains with Automated Skill Evolution