MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery
arXiv·medium signal
MLEvolve targets long-horizon ML-engineering tasks by letting LLM agents iteratively discover and refine ML algorithms rather than executing a fixed plan. It frames automated algorithm discovery as a self-evolving loop, extending the agentic-scientist line of work toward autonomous experimentation. Notable for builders watching the 'agents that improve their own pipelines' pattern that maps directly onto self-optimizing research systems.