mlsanityData to 7 Oct 2026

OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software

arXiv 2609.39903 ↗First posted 30 Sep 2026cs.AIcited by 0

On the map: Multimodal LLMs / vision-language models → Chart understanding and anomaly detection also fits: Embodied and 3D vision-language models

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Abstract (arXiv)

Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires interpreting specialized interfaces, manipulating scientific objects, and producing verifiable results. We thus introduce OSWorld-Science, a benchmark and evaluation environment that combines scientifically meaningful tasks, artifact-based evaluation, and an efficient agent harness for studying computer use in the scientific domain. The benchmark contains 12 VLMs and 146 high-quality tasks across several scientific domains and software configurations, covering workflows such as molecular drawing and retrosynthesis, pathology image analysis, statistical computing, and physical simulation. Tasks are developed through expert proposals and iterative human--AI co-design, with selection guided by scientific value and difficulty. Task-specific execution-based evaluators inspect application states and generated artifacts, including molecular structures, segmentation masks, plots, and numerical results, and award partial credit for incomplete outcomes. Our special harness integrates model adapters, interaction-loop control, and trajectory logging to support comparisons of models and interaction strategies. Our results show that current state-of-the-art VLMs with a strong harness still face challenges in addressing key questions in the scientific domains. We also analyze the benchmarking results across multi-linguistics, reasoning efforts, context length and other factors and derive several important conclusions and directions to assist future development. Overall, we provide an integrated framework connecting expert-defined scientific goals to verifiable software outcomes, enabling systematic evaluation of both agent capabilities and harness design in scientific workflows.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Chart understanding and anomaly detection, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 14 of its 46 references that are in the map. First posted on arXiv 30 Sep 2026.

Builds on

14 of 46 references.

References · 14

  1. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
  2. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,134
  3. 2024AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agentscited by 450
  4. 2024LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contextscited by 240
  5. 2024Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scalecited by 212
  6. 2023PaperQA: Retrieval-Augmented Generative Agent for Scientific Researchcited by 143
  7. 2026Kimi K3: Open Frontier Intelligencecited by 99
  8. 2025ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflowscited by 47
  9. 2024VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Taskscited by 45
  10. 2026MiniMax Sparse Attentioncited by 34
  11. 2026OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Taskscited by 29
  12. 2025OSWorld-MCP: Benchmarking MCP Tool Invocation In Computer-Use Agentscited by 25
2 more
  1. 2026Benchmarking AI Agents for Addressing Scientific Challenges Across Scalescited by 10
  2. 2026Qwen-CUA: Native Computer Use for (almost) Everythingcited by 5

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  1. 2026OSWorld-Pro: Process-based Evaluation for Computer Use Agents
  2. 2026LABBench2: An Improved Benchmark for AI Systems Performing Biology Research
  3. 2024ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
  4. 2025OSWorld-Human: Benchmarking the Efficiency of Computer-Use Agents
  5. 2024LAB-Bench: Measuring Capabilities of Language Models for Biology Research
  6. 2026Exploring LLM Agent Designs and Interaction Modalities for Scientific Visualization
  7. 2025AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
  8. 2024DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents