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Collections including paper arxiv:2608.25512
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A Programming Paradigm for Spatiotemporal Composability
Paper • 2608.25512 • Published • 19 -
On the Design Fundamentals of Pixel Text Representation Learning
Paper • 2609.01147 • Published • 30 -
Disentangling Representation Evolution in Transformers through Directional Decomposition
Paper • 2609.15975 • Published • 9 -
FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders
Paper • 2609.31620 • Published • 102
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Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling
Paper • 2507.07982 • Published • 34 -
MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh
Paper • 2508.01242 • Published • 11 -
Loc3R-VLM: Language-based Localization and 3D Reasoning with Vision-Language Models
Paper • 2603.18002 • Published • 15 -
Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding
Paper • 2603.19235 • Published • 63
-
A Programming Paradigm for Spatiotemporal Composability
Paper • 2608.25512 • Published • 19 -
On the Design Fundamentals of Pixel Text Representation Learning
Paper • 2609.01147 • Published • 30 -
Disentangling Representation Evolution in Transformers through Directional Decomposition
Paper • 2609.15975 • Published • 9 -
FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders
Paper • 2609.31620 • Published • 102
-
Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling
Paper • 2507.07982 • Published • 34 -
MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh
Paper • 2508.01242 • Published • 11 -
Loc3R-VLM: Language-based Localization and 3D Reasoning with Vision-Language Models
Paper • 2603.18002 • Published • 15 -
Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding
Paper • 2603.19235 • Published • 63