MLToolBench: Learning Tool-Augmented Agents for Machine Learning Development
Machine learning engineering (MLE) agents have made substantial progress, but learning through ML experimentation remains costly in time and computation. Synthetic environments reduce these costs while introducing variations in data and experimental settings that require task-specific diagnosis. Access to diagnostic to...
Xin Yu, Li-Zhu Zhang, Jiamu Bai et al.
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