This paper proposes a novel framework for Dynamicallyynamically regulatingdebate Relationships (DEAR) from the group perspective, and formulate the execution of the two RL-Agents as a sequential decision-making process, jointly optimizing via multi-agent reinforcement learning.
Hao Wu, Shoucheng Song, Chang Yao et al.· 0 citations
A long-term Trajectory prediction multi-scale AutoRegressive framework (TrajAR), which follows an encoder-decoder structure that progressively refines the predicted trajectory from coarse to fine scales, where coarse-scale predictions establish long-term path backbones and finer scales enhance precision.
Letian Gong, Yan Lin, Xinyue Zhang et al.· Proceedings of the Thirty-Fi...· 0 citations
Low-Rank Prior-Induced Consistency Flow Matching (LOFT) is proposed for efficient and effective distribution modeling under highly sparse data, and introduces an uncertainty-aware rectification mechanism to enable efficient inference by linearizing generative trajectories.
Xiaowei Mao, Tingrui Wu, Yawen Yang et al.· Proceedings of the 32nd ACM...· 0 citations
G-VTM, a generalized vision-trajectory model, is proposed, which captures global map semantics while modeling scenario-and direction-aware interaction based on intuitive visual perception and achieves strong generalized performance under heterogeneous traffic conditions.
Xinyue Zhang, Letian Gong, Yan Lin et al.· Proceedings of the Thirty-Fi...· 0 citations
DynaSTar is proposed, a Dynamic Spatio-Temporal Graph Invariant Learning model designed for reliable out-of-time (OOT) traffic prediction under evolving topologies, which employs a dynamic probabilistic graph structure, which is continuously refined through momentum-based updates and differentiable sparse sampling to m...
Xinyan Hao, Huai-Yu Wan, S. Guo et al.· Proceedings of the Thirty-Fi...· 0 citations
Low-Rank Prior-Induced Consistency Flow Matching (LOFT) is proposed for efficient and effective distribution modeling under highly sparse data, and introduces an uncertainty-aware rectification mechanism to enable efficient inference by linearizing generative trajectories.
Xiaowei Mao, Tingrui Wu, Yawen Yang et al.· Proceedings of the 32nd ACM...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
