view article Article Mundo: From seeing a place to simulating what happens there Luo-Yihang • 5 days ago • 61
S-Space: Exploring Spatial Workspace in Multimodal Language Models Paper • 2610.13527 • Published 19 days ago • 273
PhysFieldBench: Can Multimodal Models Understand Physical Fields? Paper • 2609.34072 • Published about 1 month ago • 1
S-Space: Exploring Spatial Workspace in Multimodal Language Models Paper • 2610.13527 • Published 19 days ago • 273
S-Space: Exploring Spatial Workspace in Multimodal Language Models Paper • 2610.13527 • Published 19 days ago • 273
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning Paper • 2608.27549 • Published Aug 27 • 49
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning Paper • 2608.27549 • Published Aug 27 • 49
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning Paper • 2608.27549 • Published Aug 27 • 49
HarnessEval-W: Agentifying the Evaluation of Visual Worlds Paper • 2608.16859 • Published Aug 17 • 342
HarnessEval-W: Agentifying the Evaluation of Visual Worlds Paper • 2608.16859 • Published Aug 17 • 342
HarnessEval-W: Agentifying the Evaluation of Visual Worlds Paper • 2608.16859 • Published Aug 17 • 342
Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context Paper • 2605.13831 • Published May 13 • 90
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models Paper • 2604.04707 • Published Apr 6 • 199
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models Paper • 2604.04707 • Published Apr 6 • 199
Thoth: Mid-Training Bridges LLMs to Time Series Understanding Paper • 2603.01042 • Published Mar 1 • 1