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INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models
Paper • 2607.26056 • Published • 18 -
DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models
Paper • 2605.03877 • Published • 3 -
Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation
Paper • 2608.17512 • Published • 54 -
MahmoodLab/UNI2-h
Image Feature Extraction • Updated • 53.1k • 304
Zhejiang University
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Papers
RoboHarness: A Simple Harness Outperforms VLA and World Action Models
More Methods, Better Agents? A Reality Check on Self-Distillation in Agentic Reinforcement Learning
Organization Card
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INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models
Paper • 2607.26056 • Published • 18 -
DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models
Paper • 2605.03877 • Published • 3 -
Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation
Paper • 2608.17512 • Published • 54 -
MahmoodLab/UNI2-h
Image Feature Extraction • Updated • 53.1k • 304
datasets 4
zju/OmniJigsaw-8K
Preview • Updated • 102 • 2
zju/gaia_grasp_bottle22249179_geo_visual100_2cam
gaia_hand_right • Updated • 100 episodes • 158
zju/sharpa_grasp_bottle22249179_geo_visual100_2cam
sharpa_hand_right • Updated • 100 episodes • 459
zju/shadow_grasp_bottle22249179_aug100_2cam
shadow_hand • Updated • 100 episodes • 183