This work converts observed trajectories and interaction cues into parsable textual prompts, so that interaction semantics are expressed more explicitly in the model input and remains competitive with recent LM-based prediction methods and strong trajectory prediction base-lines on ADE/FDE.
JEPA-WAM, a latent WAM built in a pretrained V-JEPA space, which couples latent transition prediction with continuous action generation through a shared predictor, predicts a spatially structured joint current-future target that captures task-shared visual temporal structure between current and future observations, whi...
Yi-Han Lin, Jia-Wei He, Shi-Feng Bao et al.· 12 citations· ⚡1
SimWAM, a simple yet effective WAM that leverages future-video prediction as a training-time supervision signal, co-trains a pretrained video expert and a lightweight action expert with joint flow matching and applies reinforcement learning to optimize a compositional driving reward beyond trajectory imitation.
Zongchuang Zhao, Xin Zhou, Tianyang Xu et al.· 4 citations
Trajectory prediction is essential for many robotic applications, yet most existing models rely on fixed-length observations and struggle with temporally irregular inputs. In real-world settings, prediction difficulty further increases when agents exhibit strong maneuverability, as their future motions depend on distin...
Shuobo Wang, Wen-Yuan Qin, Yong-Zhao Hua et al.· IEEE Robotics and Automation...· 0 citations
Latent-OPD is proposed, which augments OPD with trajectory-level latent distillation and introduces a progressive teacher-lookahead strategy, which aligns middle-to-late student layers with increasingly deeper teacher layers, establishing Latent-OPD as a highly effective approach to frame-efficient video reasoning.
Aoni Shen, Yongheng Zhang, Ying-Hui Li et al.· 2 citations
This work proposes a novel test-time alignment approach that leverages trajectory-guided structured sampling for dynamic inference-time refinement, achieving better alignment with visual grounding and ensuring logical consistency, and demonstrates that this approach significantly improves accuracy without incurring pro...
Tian-Bao Jiang, Wei-Cong Ni, Gerard de Melo et al.· 1 citation
