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- MLExpert: a 35B mixture-of-experts agentic model for autonomous ML engineering
An arXiv paper submitted on 15 October proposes MLExpert, a 35B mixture-of-experts agentic model trained for autonomous long-horizon machine learning engineering (MLE) optimization. The authors built the Kaggle-MLE Factory to generate executable tasks and an interaction harness, used hierarchical agentic supervised fine-tuning to transfer tool-use and coding skills, and applied Windowed Interaction RL (WIRL), which rewards the multi-turn decisions between successive experiment results as a shared execution window. The authors report that on MLE-Bench Lite MLExpert raises the base model's average medal rate from 37.9% to 72.7%, comparable to larger frontier models such as Kimi-K3 and GLM-5.3, with further gains reported on NatureBench Lite, agent scaffold optimization and algorithm optimization.
Hugging Face · Papers · 🔥 0
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