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From the 1 of 12 linked papers with an AI index.

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20242026
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12 papers

cs.ET2026

Latent Two-Sample Testing for Fair Autonomous Vehicle Road Evaluation

Qiujing Lu, Xuanhan Wang, Guanghong Jia +5

With the rapid advancement of autonomous vehicle (AV) systems, fast and reliable iteration through road testing has become increasingly critical. However, changes in testing enviro…

cs.LG2026

FAST: A Framework for Aligned Sampling and Training in Parallel Reinforcement Learning for Autonomous Driving

Bonan Wang, Letian Tao, Bin Shuai +7

The paper introduces FAST, a synchronous parallel framework that improves sampling efficiency for deep reinforcement learning in autonomous driving by aligning parallel simulations…

cs.CV2026

Teaching Vision-Language-Action Models What to See and Where to Look

Yuguang Yang, Canyu Chen, Zhewen Tan +10

Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing VLAs' training relies heavily on text-centric visual q…

cs.CV2026

DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving

Chen Shi, Jinrui Xu, Shaoshuai Shi +3

Pretrained foundation models have become an important basis for end-to-end autonomous driving. In contrast to vision-language models pretrained primarily on static image-text pairs…

cs.CL2026

STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens

Shiqi Liu, Zeyu He, Guojian Zhan +10

Reinforcement Learning (RL) has significantly improved large language model reasoning, but existing RL fine-tuning methods rely heavily on heuristic techniques such as entropy regu…

cs.RO2026

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving

Zhihua Hua, Junli Wang, Pengfei LI +6

Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental results indicate that many end-to-en…