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Cosmos 3: Omnimodal World Models for Physical AI
Paper • 2606.02800 • Published • 143 -
Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
VLANeXt: Recipes for Building Strong VLA Models
Paper • 2602.18532 • Published • 51 -
Flow-DPPO: Divergence Proximal Policy Optimization for Flow Matching Models
Paper • 2606.11025 • Published • 42
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Collections including paper arxiv:2606.06556
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Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
Imaginative Perception Tokens Enhance Spatial Reasoning in Multimodal Language Models
Paper • 2606.03988 • Published • 25 -
PhysisForcing: Physics Reinforced World Simulator for Robotic Manipulation
Paper • 2606.28128 • Published • 54 -
EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots
Paper • 2607.02646 • Published • 25
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Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
OpenSkill: Open-World Self-Evolution for LLM Agents
Paper • 2606.06741 • Published • 153 -
LLM Explainability with Counterfactual Chains and Causal Graphs
Paper • 2606.05972 • Published • 19 -
Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings
Paper • 2606.07502 • Published • 99
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CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning
Paper • 2605.28742 • Published • 4 -
Reinforcement Learning from Rich Feedback with Distributional DAgger
Paper • 2606.05152 • Published • 4 -
Entropy as a Structural Prior: How a Log-Barrier on DiT Belief Space Drives Musical Diversity and Development
Paper • 2606.07207 • Published • 4 -
Bayesian-Agent: Posterior-Guided Skill Evolution for LLM Agent Harnesses
Paper • 2606.08348 • Published • 16
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Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking
Paper • 2606.03985 • Published • 41 -
Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
Towards Scalable Pre-training of Visual Tokenizers for Generation
Paper • 2512.13687 • Published • 108 -
JEPA-Anything: Learning Predictive Models across Different Worlds
Paper • 2609.20800 • Published • 76
-
Cosmos 3: Omnimodal World Models for Physical AI
Paper • 2606.02800 • Published • 143 -
Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
VLANeXt: Recipes for Building Strong VLA Models
Paper • 2602.18532 • Published • 51 -
Flow-DPPO: Divergence Proximal Policy Optimization for Flow Matching Models
Paper • 2606.11025 • Published • 42
-
Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
Imaginative Perception Tokens Enhance Spatial Reasoning in Multimodal Language Models
Paper • 2606.03988 • Published • 25 -
PhysisForcing: Physics Reinforced World Simulator for Robotic Manipulation
Paper • 2606.28128 • Published • 54 -
EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots
Paper • 2607.02646 • Published • 25
-
CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning
Paper • 2605.28742 • Published • 4 -
Reinforcement Learning from Rich Feedback with Distributional DAgger
Paper • 2606.05152 • Published • 4 -
Entropy as a Structural Prior: How a Log-Barrier on DiT Belief Space Drives Musical Diversity and Development
Paper • 2606.07207 • Published • 4 -
Bayesian-Agent: Posterior-Guided Skill Evolution for LLM Agent Harnesses
Paper • 2606.08348 • Published • 16
-
Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
OpenSkill: Open-World Self-Evolution for LLM Agents
Paper • 2606.06741 • Published • 153 -
LLM Explainability with Counterfactual Chains and Causal Graphs
Paper • 2606.05972 • Published • 19 -
Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings
Paper • 2606.07502 • Published • 99
-
Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking
Paper • 2606.03985 • Published • 41 -
Robots Need More than VLA and World Models
Paper • 2606.06556 • Published • 31 -
Towards Scalable Pre-training of Visual Tokenizers for Generation
Paper • 2512.13687 • Published • 108 -
JEPA-Anything: Learning Predictive Models across Different Worlds
Paper • 2609.20800 • Published • 76