4 papers · 1 filter
AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation
Jiadi You, Qize Yu, Yue Chen +11
Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act. Action-labeled robot videos d…
LD4WAM: Learning Latent Dynamics from Human Videos for World Action Models
Zhenhao Shen, Jiaqi Liang, Jasper Lu +11
Human video is playing an increasingly central role in training World Action Models (WAMs), owing to its diversity and low collection cost relative to teleoperated robot data. Howe…
AffordanceVLA: A Vision-Language-Action Model Empowering Action Generation through Affordance-Aware Understanding
Qize Yu, Jiadi You, Yuran Wang +12
Vision-Language-Action (VLA) models leverage the rich world knowledge of pretrained vision-language models (VLMs) to enable instruction-following robotic manipulation. However, the…
FLUX: Accelerating Cross-Embodiment Generative Navigation Policies via Rectified Flow and Static-to-Dynamic Learning
Zeying Gong, Yangyi Zhong, Yiyi Ding +6
Autonomous navigation requires a broad spectrum of skills, from static goal-reaching to dynamic social traversal, yet evaluation remains fragmented across disparate protocols. We i…