1 citations · 1 across the 6 of their papers we have counts for
6 papers
Non-Markovian Long-Horizon Robot Manipulation via Keyframe Chaining
Yipeng Chen, Wentao Tan, Lei Zhu +4
Existing Vision-Language-Action (VLA) models often struggle to generalize to long-horizon tasks due to their heavy reliance on immediate observations. While recent studies incorpor…
Self-Correcting VLA: Online Action Refinement via Sparse World Imagination
Chenyv Liu, Wentao Tan, Lei Zhu +4
Standard vision-language-action (VLA) models rely on fitting statistical data priors, limiting their robust understanding of underlying physical dynamics. Reinforcement learning en…
MOTIF: Learning Action Motifs for Few-shot Cross-Embodiment Transfer
Heng Zhi, Wentao Tan, Lei Zhu +4
While vision-language-action (VLA) models have advanced generalist robotic learning, cross-embodiment transfer remains challenging due to kinematic heterogeneity and the high cost…
BLM: A Boundless Large Model for Cross-Space, Cross-Task, and Cross-Embodiment Learning
Wentao Tan, Bowen Wang, Heng Zhi +15
Multimodal large language models (MLLMs) have advanced vision-language reasoning and are increasingly deployed in embodied agents. However, significant limitations remain: MLLMs ge…
Style Interleaved Learning for Generalizable Person Re-identification
Wentao Tan, Changxing Ding, Pengfei Wang +2
Domain generalization (DG) for person re-identification (ReID) is a challenging problem, as access to target domain data is not permitted during the training process. Most existing…
Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification
Pengfei Wang, Changxing Ding, Wentao Tan +3
Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims at adapting a model trained on a labeled source domain to an unlabeled target domain. State-of-the-art obje…