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

---
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