12 papers · 1 filter
Relational Geometry Forcing for World Action Models
Yuan Xu, Yixiang Chen, Qisen Ma +10
World Action Models (WAMs) have shown strong potential for robot manipulation by jointly learning visual dynamics and executable actions. However, their video and action objectives…
What Matters for World Modeling in Vision-Language-Action Models?
Qisen Ma, Yixiang Chen, Yuan Xu +10
Integrating world models into Vision-Language-Action models (VLAs) has emerged as a promising direction, enabling policies to anticipate future dynamics beyond reactive observation…
XEWorld: Can Action-Conditioned World Models Generalize to Unseen Robot Embodiments?
Yixiang Chen, Jiabing Yang, Yuan Xu +10
Action-conditioned world models are promising learned simulators for robotic manipulation, yet evaluating them exclusively on training robots fails to reveal whether they capture p…
BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation
Peiyan Li, Yuze Zhu, Yixiang Chen +10
Leveraging pre-trained vision-language models (VLMs) to construct vision-language-action (VLA) models has emerged as a promising paradigm for 3D robot manipulation. However, existi…
FlowWAM: Optical Flow as a Unified Action Representation for World Action Models
Yixiang Chen, Peiyan Li, Yuan Xu +13
World Action Models (WAMs) are able to leverage pretrained video generators for both world modeling and action prediction. However, directly leveraging such video generators for co…
DIM-WAM: World-Action Modeling with Diverse Historical Event Memory
Kai Wang, Zhaopeng Gu, Yixiang Chen +7
World-action models have shown promising robot-manipulation performance by jointly predicting future visual states and actions. However, existing methods mainly rely on short-term…
E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation
Wen Ye, Peiyan Li, Tingyu Yuan +7
Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reasoning can effectively improve t…
WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation
Ning Yang, Yan Huang, Kaiwen Peng +9
Visual navigation requires generating smooth and collision-free trajectories under complex geometric and physical constraints. Existing reactive policies that directly map observat…
Efficient-WAM: A 1B-Parameter World-Action Model with Low-Cost Future Imagination
Jiajun Li, Tiecheng Guo, Yifan Ye +10
World-Action Models (WAMs) have emerged as a promising paradigm for embodied control by coupling future visual prediction with action generation. However, many existing WAMs rely o…
SKIP: Sparse Keyframe Interpolation Paradigm for Efficient Embodied World Models
Ziheng He, Yixiang Chen, Ning Yang +11
Embodied world models have emerged as a promising paradigm in robotics by predicting how robot actions affect the surrounding scene. However, the rollout inference remains computat…
BridgeV2W: Bridging Video Generation Models to Embodied World Models via Embodiment Masks
Yixiang Chen, Peiyan Li, Jiabing Yang +8
Embodied world models have emerged as a promising paradigm in robotics, most of which leverage large-scale Internet videos or pretrained video generation models to enrich visual an…
UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations
Tingyu Yuan, Biaoliang Guan, Wen Ye +8
In embodied intelligence, the embodiment gap between robotic and human hands brings significant challenges for learning from human demonstrations. Although some studies have attemp…