S-Space: Exploring Spatial Workspace in Multimodal Language Models Paper • 2610.13527 • Published 4 days ago • 272
PhysFieldBench: Can Multimodal Models Understand Physical Fields? Paper • 2609.34072 • Published 16 days ago
S-Space: Exploring Spatial Workspace in Multimodal Language Models Paper • 2610.13527 • Published 4 days ago • 272
Nano World Models: A Minimalist Implementation of Future Video Prediction Paper • 2605.23993 • Published May 27
OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining Paper • 2609.07398 • Published Sep 7 • 80
HarnessEval-W: Agentifying the Evaluation of Visual Worlds Paper • 2608.16859 • Published Aug 17 • 122
OMG: Omni-Modal Motion Generation for Generalist Humanoid Control Paper • 2606.10340 • Published Jun 9
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI Paper • 2605.08678 • Published May 9 • 9
OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining Paper • 2609.07398 • Published Sep 7 • 80
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning Paper • 2608.27549 • Published Aug 27 • 48
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning Paper • 2608.27549 • Published Aug 27 • 48
HarnessEval-W: Agentifying the Evaluation of Visual Worlds Paper • 2608.16859 • Published Aug 17 • 122
HarnessEval-W: Agentifying the Evaluation of Visual Worlds Paper • 2608.16859 • Published Aug 17 • 122
Time Series Foundation Models Collection Pretrained models for intelligent and out-of-the-box time series forecasting • 8 items • Updated Jun 6 • 16
Thoth: Mid-Training Bridges LLMs to Time Series Understanding Paper • 2603.01042 • Published Mar 1 • 1
OpenWorldLib: A Unified Codebase and Definition of Advanced World Models Paper • 2604.04707 • Published Apr 6 • 199