Reproduce “AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research” on OpenResearch

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About this paper

Yilun Zhao, Weiyuan Chen, Zhijian Xu, Manasi Patwardhan, Yixin Liu, Chengye Wang, Lovekesh Vig, Arman Cohan

AbGen benchmarks the design of ablation studies by asking models to propose experiments for named components from research context. It includes 1,500 examples from 807 NLP papers. Models draft tests, but automated scores nearly tie leading models. DeepSeek-R1-0528 scores 4.11/5 on human evaluation, below the expert estimate of 4.80/5. These results assess design, not experiment execution.

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