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 • 31
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 4 days ago • 26
CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents Paper • 2605.25624 • Published 4 days ago • 26
CUA-Suite: Massive Human-annotated Video Demonstrations for Computer-Use Agents Paper • 2603.24440 • Published Mar 25 • 98
VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos Paper • 2510.19488 • Published Oct 22, 2025 • 22
Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization Paper • 2510.13554 • Published Oct 15, 2025 • 59