9 citations · 10 across the 4 of their papers we have counts for
4 papers
Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding
Hayate Iso, Tiyasa Mitra, Sudipta Mondal +15
RL post-training of frontier language models is increasingly bottlenecked by autoregressive rollout generation, making rollout acceleration a central systems challenge. Many existi…
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling
Zikang Zhou, Hengjian Zhou, Haibo Hu +4
Anticipating the multimodality of future events lays the foundation for safe autonomous driving. However, multimodal motion prediction for traffic agents has been clouded by the la…
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
Zikang Zhou, Haibo Hu, Xinhong Chen +6
Simulating realistic behaviors of traffic agents is pivotal for efficiently validating the safety of autonomous driving systems. Existing data-driven simulators primarily use an en…
QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction
Zikang Zhou, Zihao Wen, Jianping Wang +2
Estimating the joint distribution of on-road agents' future trajectories is essential for autonomous driving. In this technical report, we propose a next-generation framework for j…