Collections
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Collections including paper arxiv:2501.03575
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Cosmos World Foundation Model Platform for Physical AI
Paper • 2501.03575 • Published • 81 -
Phi-4 Technical Report
Paper • 2412.08905 • Published • 122 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 300 -
DeepSeek-V3 Technical Report
Paper • 2412.19437 • Published • 71
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Cosmos World Foundation Model Platform for Physical AI
Paper • 2501.03575 • Published • 81 -
Intuitive physics understanding emerges from self-supervised pretraining on natural videos
Paper • 2502.11831 • Published • 20 -
PhysicsGen: Can Generative Models Learn from Images to Predict Complex Physical Relations?
Paper • 2503.05333 • Published • 8 -
Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning
Paper • 2503.15558 • Published • 50
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Video Creation by Demonstration
Paper • 2412.09551 • Published • 9 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 48 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 72 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38
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Cosmos World Foundation Model Platform for Physical AI
Paper • 2501.03575 • Published • 81 -
VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM
Paper • 2501.00599 • Published • 47 -
OmniManip: Towards General Robotic Manipulation via Object-Centric Interaction Primitives as Spatial Constraints
Paper • 2501.03841 • Published • 56 -
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
Paper • 2501.04003 • Published • 27
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MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Paper • 2501.02955 • Published • 44 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 85 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 28
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RL Zero: Zero-Shot Language to Behaviors without any Supervision
Paper • 2412.05718 • Published • 5 -
Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 38 -
Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning
Paper • 2412.15797 • Published • 18 -
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper • 2412.18319 • Published • 39
-
Cosmos World Foundation Model Platform for Physical AI
Paper • 2501.03575 • Published • 81 -
VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM
Paper • 2501.00599 • Published • 47 -
OmniManip: Towards General Robotic Manipulation via Object-Centric Interaction Primitives as Spatial Constraints
Paper • 2501.03841 • Published • 56 -
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
Paper • 2501.04003 • Published • 27
-
Cosmos World Foundation Model Platform for Physical AI
Paper • 2501.03575 • Published • 81 -
Phi-4 Technical Report
Paper • 2412.08905 • Published • 122 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 300 -
DeepSeek-V3 Technical Report
Paper • 2412.19437 • Published • 71
-
Cosmos World Foundation Model Platform for Physical AI
Paper • 2501.03575 • Published • 81 -
Intuitive physics understanding emerges from self-supervised pretraining on natural videos
Paper • 2502.11831 • Published • 20 -
PhysicsGen: Can Generative Models Learn from Images to Predict Complex Physical Relations?
Paper • 2503.05333 • Published • 8 -
Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning
Paper • 2503.15558 • Published • 50
-
MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Paper • 2501.02955 • Published • 44 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 85 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 28
-
Video Creation by Demonstration
Paper • 2412.09551 • Published • 9 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 48 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 72 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38
-
RL Zero: Zero-Shot Language to Behaviors without any Supervision
Paper • 2412.05718 • Published • 5 -
Offline Reinforcement Learning for LLM Multi-Step Reasoning
Paper • 2412.16145 • Published • 38 -
Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning
Paper • 2412.15797 • Published • 18 -
Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Paper • 2412.18319 • Published • 39