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Image Credit: Arxiv

ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery

  • ScienceAgentBench is a benchmark for evaluating language agents for data-driven scientific discovery.
  • It aims to assess the capabilities of large language models (LLMs) in automating scientific discovery tasks.
  • The benchmark includes 102 tasks extracted from peer-reviewed publications in four disciplines, with validation from subject matter experts.
  • Results show that current language agents have limitations in generating code for data-driven discovery and end-to-end automation of scientific research.

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