mlsanityData to 14 Oct 2026

Gravity-Bench-v1: A Benchmark on Gravitational Physics Discovery for Agents

arXiv 2501.18411 ↗First posted 30 Jan 2025cs.AI astro-ph.IM physics.comp-phcited by 13

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Abstract (arXiv)

Modern science emerged from reasoning over repeatedly-observed planetary motions. We present Gravity-Bench-v1, an environment-based benchmark that challenges AI agents on tasks that parallel this historical development. Gravity-Bench-v1 evaluates agents on the discovery of physics concealed within a dynamic environment, using rigorous gravitational dynamics simulations. Gravity-Bench includes out-of-distribution cases, i.e. with physics that deviates from the real world, to evaluate true scientific generalization capabilities. Agents must plan to collect data within an experimental budget and must perform a dynamic form of data analysis and reasoning to solve tasks efficiently. Our benchmark admits an open-ended space of solutions. Reference solutions for each task are provided to calibrate AI performance against human expertise. Technically at an upper-undergraduate level, our benchmark proves challenging to baseline AI agents. Gravity-Bench-v1 and planned extensions should help map out AI progress towards scientific discovery capabilities.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 14 of its 36 references that are in the map. First posted on arXiv 30 Jan 2025.

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14 of 36 references.

References · 14

  1. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
  2. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,886
  3. 2019HellaSwag: Can a Machine Really Finish Your Sentence?cited by 4,100
  4. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  5. 2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,879
  6. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
  7. 2024Large Language Monkeys: Scaling Inference Compute with Repeated Samplingcited by 991
  8. 2024ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Modelscited by 210
  9. 2024LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discoverycited by 86
  10. 2025LLM4SR: A Survey on Large Language Models for Scientific Researchcited by 83
  11. 2022Rediscovering orbital mechanics with machine learningcited by 71
  12. 2020A Bayesian machine scientist to aid in the solution of challenging scientific problemscited by 61
2 more
  1. 2024SciDFM: A Large Language Model with Mixture-of-Experts for Sciencecited by 7
  2. 2021Approximation Methods for Partially Observed Markov Decision Processes (POMDPs)cited by 1

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