agent/papers/items/2026-2606-06473-mlevolve-a-self-evolving-framework-for-automated-machine-learning-algorithm-disc.md

Paper: MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery

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type: paper title: "MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery" authors: Shangheng Du, Xiangchao Yan, Jinxin Shi, Zongsheng Cao, Shiyang Feng, Zichen Liang, Boyuan Sun, Tianshuo Peng, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.06473 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-04 updated_at: 2026-06-04 status: queued relevance: high topics:

• agent-evaluation
• coding-agent
• memory
• multi-agent
• planning
• rag methods:

benchmarks:

models:

datasets:

• cs.AI
• cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 14 collection_queries: planning-agent

One-line Takeaway

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

Why Collected

• matched queries: planning-agent
• inferred topics: agent-evaluation, coding-agent, memory, multi-agent, planning, rag
• arXiv categories: cs.AI, cs.CL
• collection score: 14

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/2606.06473