From the 1 of 11 linked papers with an AI index.
11 papers
How Can Driving World Models Do Counterfactual Prediction?
Jiaru Zhang, Can Cui, Yi Xu +3
Driving world models are often interpreted as counterfactual simulators for observed driving episodes: given a factual driving log, they are asked what would have happened under an…
Post-Training in End-to-End Autonomous Driving
Ruining Yang, Muxing Wang, Yixiao Chen +8
This survey reviews post‑training methods that refine end‑to‑end autonomous driving models beyond imitation, organizing existing work into four families based on the type of superv…
Out-of-Sight Embodied Agents: Multimodal Tracking, Sensor Fusion, and Trajectory Forecasting
Haichao Zhang, Yi Xu, Yun Fu
Trajectory prediction is a fundamental problem in computer vision, vision-language-action models, world models, and autonomous systems, with broad impact on autonomous driving, rob…
Den-TP: A Density-Balanced Data Curation and Evaluation Framework for Trajectory Prediction
Ruining Yang, Yi Xu, Yun Fu +1
Trajectory prediction in autonomous driving has traditionally been studied from a model-centric perspective. However, existing datasets exhibit a strong long-tail distribution in s…
SHIELD: Suppressing Hallucinations In LVLM Encoders via Bias and Vulnerability Defense
Yiyang Huang, Liang Shi, Yitian Zhang +2
Large Vision-Language Models (LVLMs) excel in diverse cross-modal tasks. However, object hallucination, where models produce plausible but inaccurate object descriptions, remains a…
Trajectory Prediction Meets Large Language Models: A Survey
Yi Xu, Ruining Yang, Yitian Zhang +5
Recent advances in large language models (LLMs) have sparked growing interest in integrating language-driven techniques into trajectory prediction. By leveraging their semantic and…