| 1 |
G$^2$ARD-GS: Geometry-Guided Anchor-Regularized Gaussian Splatting Distillation |
提出G$^2$ARD-GS以解决稠密LiDAR地图的高存储成本问题 |
distillation 3D gaussian splatting 3DGS |
✅ |
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| 2 |
Bar-JEPA: Extracting Values from Bar Chart with Joint-Embedding Predictive Architecture |
提出Bar-JEPA以解决条形图数据提取问题 |
JEPA Joint-Embedding Predictive Architecture joint-embedding predictive architecture |
✅ |
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| 3 |
Learning from Failures: Retrieval-Centric CoT via Hard Negatives for Unified Multimodal Retrieval |
提出UniME-R1以解决多模态检索中的理解偏差问题 |
reinforcement learning multimodal chain-of-thought |
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| 4 |
Wan-Animate-2: Pushing the Application Boundaries of Character Animation |
提出Wan-Animate-2以解决角色动画实时性与精度问题 |
distillation motion representation character animation |
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| 5 |
LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models |
提出LAWM-3D以解决机器人世界模型中的3D感知问题 |
world model world models foundation model |
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| 6 |
HERA: Historical Evidence Routing Adapter for Physical Prediction in Latent World Models |
提出HERA以解决物理预测中的历史证据访问问题 |
world model world models JEPA |
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| 7 |
MASS: Multiplayer World Models with Authoritative Shared State |
提出MAS以解决多玩家环境中的世界模型问题 |
world model world models |
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| 8 |
Uncertainty-Aware World Model for Aerial Image-Goal Navigation |
提出不确定性感知世界模型以解决无人机图像目标导航问题 |
world model world models |
✅ |
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| 9 |
Curia-MAE: Multi-Modal Multi-Anatomy MAE Pre-Training for 3D Medical Image Segmentation |
提出Curia-MAE以提升3D医学图像分割性能 |
MAE foundation model |
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| 10 |
SR-JEPA: Learning Predictive Latent State in 3D Scenes |
提出SR-JEPA以解决3D场景中缺失实体的预测问题 |
JEPA Joint-Embedding Predictive Architecture joint-embedding predictive architecture |
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| 11 |
ChronoVision: Temporal Reasoning via Latent State Reconstruction |
提出ChronoVision以解决多步时间推理问题 |
reinforcement learning large language model multimodal |
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| 12 |
The Next Screenshot Knows: Gated Hindsight Distillation for Mobile GUI Agents |
提出Gated Hindsight Distillation以解决GUI代理训练中的信息缺失问题 |
distillation privileged information |
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| 13 |
Flow-Map Distillation on Relation Manifolds for Image Restoration |
提出Flow-Map蒸馏方法以提升图像恢复性能 |
flow matching distillation |
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| 14 |
Hierarchical Flow Matching for 3D Point Cloud Generation |
提出层次流匹配方法以生成高质量3D点云 |
flow matching |
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| 15 |
Dense-Cast: A lightweight ensemble of deep learning architectures for precipitation nowcasting |
提出Dense-Cast以解决降水短期预报问题 |
MAE spatiotemporal |
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| 16 |
SLED: Scalable Location Encoding via Distillation |
提出SLED以解决地理空间数据编码效率低的问题 |
distillation spatiotemporal multimodal |
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| 17 |
Curia-MAE: Multi-Modal Multi-Anatomy MAE Pre-Training for 3D Medical Image Segmentation |
提出Curia-MAE以提升3D医学图像分割性能 |
MAE foundation model |
✅ |
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| 18 |
InsertFuse: A Unified Framework for Multi-Category Reference-Guided Image Insertion |
提出InsertFuse框架以解决多类别参考引导图像插入问题 |
flow matching distillation |
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