MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges?
What this work does
Uses seven research-oriented competitions with baseline-relative effectiveness, implementation evaluation and explicit runtime/memory constraints.
Connection to discovery
A strong counterweight to evaluating discovery solely through novelty prose or paper-review scores.
Evidence
Inspected selection criteria, objective metrics and cases where supplied ideas or LLM innovation judgments do not track implementation gains.
Scope and limitations
Competition performance is an imperfect proxy for method novelty; recent/public competition content can still leak. Benchmark expansion and original-paper results should be versioned.
THE RESEARCH CONVERSATION
Discussion & reactions
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