most citedLarge Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Kimi K3: Open Frontier Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +398

We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…

cs.CV2026

MuRA: Multi-Rank Adaptation for Efficient and Effective Test-Time Vision-Language Generalization

Gengyuan Liu, Nanzhou Wang, Chang Liu +5

Vision-language models exhibit remarkable zero-shot capabilities but suffer significant performance degradation under distribution shifts. While test-time adaptation (TTA) via Low-…

cs.RO2026

PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment

Chuancheng Zhang, Zhenhao Wang, Kaizheng Li +3

Real-world autonomous driving, particularly in urban environments with numerous corner cases, requires rigorous testing to ensure product safety and robustness. However, few studie…

cs.RO2025★ 1 cited

Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey

Wei Dai, Shengen Wu, Wei Wu +7

Trajectory prediction serves as a critical functionality in autonomous driving, enabling the anticipation of future motion paths for traffic participants such as vehicles and pedes…

cs.RO2025

Generative Modeling for Adversarial Lane-Change Scenarios

Chuancheng Zhang, Zhenhao Wang, Jiangcheng Wang +5

Decision-making in long-tail scenarios is pivotal to autonomous-driving development, and realistic and challenging simulations play a crucial role in testing safety-critical situat…