Distilling Physical Priors into Streaming World Models | Paper Citation Record

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Distilling Physical Priors into Streaming World Models IEEE Transactions on Pattern Analysis and Machine Intelligence , year=

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Distilling Physical Priors into Streaming World Models Advances in Neural Information Processing Systems , volume=

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Distilling Physical Priors into Streaming World Models Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

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Distilling Physical Priors into Streaming World Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

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Distilling Physical Priors into Streaming World Models Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

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Distilling Physical Priors into Streaming World Models Proceedings of the 41st International Conference on Machine Learning , year=

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Distilling Physical Priors into Streaming World Models Advances in Neural Information Processing Systems , year=

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Distilling Physical Priors into Streaming World Models International Conference on Learning Representations , year=

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Distilling Physical Priors into Streaming World Models Test-Time Training Done Right

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Distilling Physical Priors into Streaming World Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , year=

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Distilling Physical Priors into Streaming World Models Proceedings of the 42nd International Conference on Machine Learning , series=

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Distilling Physical Priors into Streaming World Models Long-Context Autoregressive Video Modeling with Next-Frame Prediction

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Distilling Physical Priors into Streaming World Models Proceedings of the 41st International Conference on Machine Learning , pages=

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Distilling Physical Priors into Streaming World Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

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Distilling Physical Priors into Streaming World Models MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft

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Distilling Physical Priors into Streaming World Models LongLive: Real-time Interactive Long Video Generation

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Distilling Physical Priors into Streaming World Models Yume: An Interactive World Generation Model

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Distilling Physical Priors into Streaming World Models 2512.22096 , archivePrefix=

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Distilling Physical Priors into Streaming World Models Advancing Open-source World Models

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Distilling Physical Priors into Streaming World Models URL: https://deepmind

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Distilling Physical Priors into Streaming World Models V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

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Distilling Physical Priors into Streaming World Models VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation

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Distilling Physical Priors into Streaming World Models OpenVLA: An Open-Source Vision-Language-Action Model

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Distilling Physical Priors into Streaming World Models Dreamitate: Real-World Visuomotor Policy Learning via Video Generation

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Distilling Physical Priors into Streaming World Models DreamGen: Unlocking Generalization in Robot Learning through Video World Models

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Distilling Physical Priors into Streaming World Models mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs

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Distilling Physical Priors into Streaming World Models World Action Models are Zero-shot Policies

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Distilling Physical Priors into Streaming World Models 2024 , howpublished=

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Distilling Physical Priors into Streaming World Models Cosmos World Foundation Model Platform for Physical AI

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Distilling Physical Priors into Streaming World Models 1967 , publisher=

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Distilling Physical Priors into Streaming World Models Video models are zero-shot learners and reasoners

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Distilling Physical Priors into Streaming World Models Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations

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Distilling Physical Priors into Streaming World Models Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

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Distilling Physical Priors into Streaming World Models LuciBot: Automated Robot Policy Learning from Generated Videos

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Distilling Physical Priors into Streaming World Models Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation

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Distilling Physical Priors into Streaming World Models VideoAgent: Self-Improving Video Generation

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Distilling Physical Priors into Streaming World Models DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge

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Distilling Physical Priors into Streaming World Models Ctrl-World: A Controllable Generative World Model for Robot Manipulation

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Distilling Physical Priors into Streaming World Models 2511.11520 , archivePrefix=

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Distilling Physical Priors into Streaming World Models Acm siggraph 2016 courses , pages=

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Distilling Physical Priors into Streaming World Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

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Observation 67d6e955-646c-4f0e-9127-0f701c224708 · outbound

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Reference 69

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Observation 4a21f3f7-867a-40b6-97f2-f0859aab25d8 · outbound

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Reference 71

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Distilling Physical Priors into Streaming World Models Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling

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Reference 75

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Reference 76

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Observation ccf33a75-32a0-478e-8da9-00661a67318b · outbound

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Reference 77

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Observation 685a16fc-327d-4c6d-90ac-7cf9c4639826 · outbound

This paper cites an unresolved cited work.

Distilling Physical Priors into Streaming World Models Unresolved cited work

Reference 78

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Distilling Physical Priors into Streaming World Models Enhancing Physical Plausibility in Video Generation by Reasoning the Implausibility

Reference 80

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Observation fee5c7ed-2edf-4a11-9b12-fa63a8834946 · outbound

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Observation c2345817-fc7e-450f-9c80-1575680f5bb2 · outbound

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Reference 82

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Observation 2da5a490-9276-4617-9d6e-3a594ee02f1e · outbound

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Reference 83

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Observation db2b2f19-a951-42c1-9c6d-ed0791314a90 · outbound

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Reference 84

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Observation bc88d199-84e7-4c3c-b5a2-eddc4c91101a · outbound

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Distilling Physical Priors into Streaming World Models Unresolved cited work

Reference 85

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Observation 440247a2-ec81-40c1-87f6-ed48b9b0151b · outbound

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Distilling Physical Priors into Streaming World Models Unresolved cited work

Reference 86

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Observation 8d791e96-a73b-42d5-a2b0-9c994a61d1a8 · outbound

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Distilling Physical Priors into Streaming World Models Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning

Reference 87

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Observation 0ca86988-fffa-44af-a1b4-e9e0da9ebf0b · outbound

This paper cites an unresolved cited work.

Distilling Physical Priors into Streaming World Models Unresolved cited work

Reference 88

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Observation 4b6d6780-c8e6-4eb0-ac24-9a1fb24d230e · outbound

This paper cites an unresolved cited work.

Distilling Physical Priors into Streaming World Models Unresolved cited work

Reference 89

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Observation 8f2f6a9e-c781-4c42-8789-57db9d888e5c · outbound

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Reference 90

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Observation e9a4aa6d-f4de-4833-ab37-e3c15eb88851 · outbound

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Reference 92

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Observation 41491c0d-2484-4bb4-973f-3762f9422860 · outbound

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Reference 93

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Observation 3aaaf8f7-80cb-49ba-83a8-a62b2f6e34f3 · outbound

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Distilling Physical Priors into Streaming World Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 94

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Observation 5daa38a3-0726-4a30-9d8a-966825940e85 · outbound

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Reference 95

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Observation aa0b2617-32d2-48d9-969b-0bd6b9002278 · outbound

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Distilling Physical Priors into Streaming World Models DanceGRPO: Unleashing GRPO on Visual Generation

Reference 96

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Observation dddd4ff7-c8e3-4583-bb5d-19454f008a6f · outbound

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Distilling Physical Priors into Streaming World Models 2603.17051 , archivePrefix=

Reference 97

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Observation e31febc5-69ed-4669-a19c-ebf21c33c969 · outbound

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Distilling Physical Priors into Streaming World Models KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration

Reference 98

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Observation afa3b29a-9bff-4653-8183-8e9e311c327b · outbound

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Distilling Physical Priors into Streaming World Models Flow Matching for Generative Modeling

Reference 99

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Observation fdcf0fb3-e70f-4254-addf-fe4ff2e83f9b · outbound

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Reference 100

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Pith citing papers