DARE-bench: Evaluating Modeling and Instruction Fidelity of LLMs in Data Science

Fan Shu, Yite Wang, Ruofan Wu, Boyi Liu, Zhewei Yao et al.|February 27, 2026arXiv

Key Takeaway

LLMs need specialized training data to reliably follow data science workflows; fine-tuning on task-specific benchmarks can improve performance by 8x.

Summary

DARE-bench is a benchmark for testing how well AI models can follow data science instructions and complete multi-step ML tasks. It includes 6,300 real Kaggle tasks with verifiable correct answers, making evaluation objective rather than relying on human judges.

evaluation training applications

Key Terms

fine-tuning reinforcement-learning instruction-following benchmark