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agent/papers/items/2026-2605-27366-muse-autoskill-self-evolving-agents-via-skill-creation-memory-management-and-eva.md
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# Paper: MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation
---
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