MLE-Bench
PulseAugur coverage of MLE-Bench — every cluster mentioning MLE-Bench across labs, papers, and developer communities, ranked by signal.
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iML framework enhances AutoML with executable, problem-grounded code
Researchers have introduced iML, a new framework for code-driven Automated Machine Learning (AutoML). iML addresses limitations in current AutoML systems by focusing on generating executable, problem-grounded, and broad…
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FML-Bench benchmark questions algorithmic progress in ML research
A new benchmark called FML-Bench suggests that recent gains in automated machine learning research, specifically in areas like code editing agents, are not primarily due to algorithmic advancements. When controlling for…
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New MLEvolve framework automates ML algorithm discovery
Researchers have developed MLEvolve, a novel LLM-based multi-agent framework designed for automated machine learning algorithm discovery. This framework improves upon existing methods by addressing information isolation…