3 citations · 6 across the 9 of their papers we have counts for
10 papers
ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving
Zhiyuan Zhang, Yanlun Peng, Jianing Zhang +7
Reactive capability is a key property of data-driven behavior world model simulators for autonomous driving simulation systems. With this capability, simulated world agents can res…
TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge
Zhiyuan Zhang, Xiaosong Jia, Guanyu Chen +2
In this technical report, we introduce TrajTok, a trajectory tokenizer for discrete next-token-prediction based behavior generation models, which combines data-driven and rule-base…
Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)
Zhenjie Yang, Xiaosong Jia, Qifeng Li +3
Reinforcement Learning (RL) can mitigate the causal confusion and distribution shift inherent to imitation learning (IL). However, applying RL to end-to-end autonomous driving (E2E…
DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving
Zhenjie Yang, Yilin Chai, Xiaosong Jia +5
End-to-end autonomous driving (E2E-AD) demands effective processing of multi-view sensory data and robust handling of diverse and complex driving scenarios, particularly rare maneu…
Automatically Planning Optimal Parallel Strategy for Large Language Models
Zongbiao Li, Xiezhao Li, Yinghao Cui +11
The number of parameters in large-scale language models based on transformers is gradually increasing, and the scale of computing clusters is also growing. The technology of quickl…
An Unsupervised Dialogue Topic Segmentation Model Based on Utterance Rewriting
Xia Hou, Qifeng Li, Tongliang Li
Dialogue topic segmentation plays a crucial role in various types of dialogue modeling tasks. The state-of-the-art unsupervised DTS methods learn topic-aware discourse representati…
Raw Text is All you Need: Knowledge-intensive Multi-turn Instruction Tuning for Large Language Model
Xia Hou, Qifeng Li, Jian Yang +8
Instruction tuning as an effective technique aligns the outputs of large language models (LLMs) with human preference. But how to generate the seasonal multi-turn dialogues from ra…
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
Xiaosong Jia, Zhenjie Yang, Qifeng Li +2
In an era marked by the rapid scaling of foundation models, autonomous driving technologies are approaching a transformative threshold where end-to-end autonomous driving (E2E-AD)…
Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2)
Qifeng Li, Xiaosong Jia, Shaobo Wang +1
Real-world autonomous driving (AD) especially urban driving involves many corner cases. The lately released AD simulator CARLA v2 adds 39 common events in the driving scene, and pr…
End-to-End Streaming Video Temporal Action Segmentation with Reinforce Learning
Jinrong Zhang, Wujun Wen, Shenglan Liu +3
The streaming temporal action segmentation (STAS) task, a supplementary task of temporal action segmentation (TAS), has not received adequate attention in the field of video unders…