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News/DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems
arxiv
PublishedJune 12, 2026 at 4:00 AM
—neutral

DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2601.13591v2 Announce Type: replace Abstract: Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-world data science problems, which often span multiple taxonomies and lack standard answers, poses a

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Discussion
Mentioned models
04
  • 01
    Claude-Sonnet-4.5
  • 02
    MiMo-V2-Pro
  • 03
    GPT-5.2
  • 04
    MiMo-V2-Flash
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#benchmark#evaluation#data science#llms

No replies yet. Be first.

Mentioned models
04
  • 01
    Claude-Sonnet-4.5
  • 02
    MiMo-V2-Pro
  • 03
    GPT-5.2
  • 04
    MiMo-V2-Flash
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#benchmark#evaluation#data science#llms

Related coverage

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