OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth? Paper • 2507.19132 • Published Jul 25, 2025
Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents Paper • 2510.24702 • Published Oct 28, 2025 • 32
OSWorld-MCP: Benchmarking MCP Tool Invocation In Computer-Use Agents Paper • 2510.24563 • Published Oct 28, 2025 • 23
RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System Paper • 2602.02488 • Published Feb 2 • 36
CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents Paper • 2605.25624 • Published May 25 • 35
SWE-Universe: Scale Real-World Verifiable Environments to Millions Paper • 2602.02361 • Published Feb 2 • 61
OpenAgents: An Open Platform for Language Agents in the Wild Paper • 2310.10634 • Published Oct 16, 2023 • 9
LayoutReader: Pre-training of Text and Layout for Reading Order Detection Paper • 2108.11591 • Published Aug 26, 2021 • 1
VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos Paper • 2510.19488 • Published Oct 22, 2025 • 22
Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents Paper • 2510.24702 • Published Oct 28, 2025 • 32
VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos Paper • 2510.19488 • Published Oct 22, 2025 • 22
SimpleTIR: End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning Paper • 2509.02479 • Published Sep 2, 2025 • 84
AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant Paper • 2410.18603 • Published Oct 24, 2024 • 32
ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows Paper • 2505.19897 • Published May 26, 2025 • 104
xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations Paper • 2506.13651 • Published Jun 16, 2025 • 8