agent/papers/items/2026-2605-27366-muse-autoskill-self-evolving-agents-via-skill-creation-memory-management-and-eva.md

Paper: MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation

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type: paper title: "MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation" authors: Huawei Lin, Peng Li, Jie Song, Fuxin Jiang, Tieying Zhang year: 2026 venue: arXiv url: https://arxiv.org/abs/2605.27366 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-26 updated_at: 2026-07-03 status: queued relevance: high topics:

• agent-evaluation
• memory methods:

benchmarks:

models:

datasets:

• cs.AI
• cs.CL
• cs.LG
• cs.MA related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 15 collection_queries: agent-memory

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-memory
• inferred topics: agent-evaluation, memory
• arXiv categories: cs.AI, cs.CL, cs.LG, cs.MA
• collection score: 15

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2605.27366