most citedReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

cs.RO2026

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives

Junli Wang, Zhihua Hua, Xueyi Liu +7

Existing imitation learning methods for end-to-end autonomous driving predominantly learn from successful demonstrations by minimizing geometric deviations from expert trajectories…

cs.CV2026

Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation

Jinghui Lu, Jiayi Guan, Zhijian Huang +47

Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature imposes a latency cost that is…

cs.RO2026

PerlAD: Towards Enhanced Closed-loop End-to-end Autonomous Driving with Pseudo-simulation-based Reinforcement Learning

Yinfeng Gao, Qichao Zhang, Deqing Liu +8

End-to-end autonomous driving policies based on Imitation Learning (IL) often struggle in closed-loop execution due to the misalignment between inadequate open-loop training object…

cs.RO2026

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving

Yinan Zheng, Tianyi Tan, Bin Huang +11

Diffusion models have become a popular choice for decision-making tasks in robotics, and more recently, are also being considered for solving autonomous driving tasks. However, the…

cs.CV2025

TrajMoE: Scene-Adaptive Trajectory Planning with Mixture of Experts and Reinforcement Learning

Zebin Xing, Pengxuan Yang, Linbo Wang +12

Current autonomous driving systems often favor end-to-end frameworks, which take sensor inputs like images and learn to map them into trajectory space via neural networks. Previous…

cs.CV2025

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

Tianze Xia, Yongkang Li, Lijun Zhou +9

World models have become crucial for autonomous driving, as they learn how scenarios evolve over time to address the long-tail challenges of the real world. However, current approa…

cs.RO2025

MiMo-Embodied: X-Embodied Foundation Model Technical Report

Xiaoshuai Hao, Lei Zhou, Zhijian Huang +41

We open-source MiMo-Embodied, the first cross-embodied foundation model to successfully integrate and achieve state-of-the-art performance in both Autonomous Driving and Embodied A…

cs.CV2025

WorldSplat: Gaussian-Centric Feed-Forward 4D Scene Generation for Autonomous Driving

Ziyue Zhu, Zhanqian Wu, Zhenxin Zhu +8

Recent advances in driving-scene generation and reconstruction have demonstrated significant potential for enhancing autonomous driving systems by producing scalable and controllab…

cs.CV2025★ 1 cited

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving

Yongkang Li, Kaixin Xiong, Xiangyu Guo +12

Recent studies have explored leveraging the world knowledge and cognitive capabilities of Vision-Language Models (VLMs) to address the long-tail problem in end-to-end autonomous dr…