3 papers
cs.CV2026
Generative Scenario Rollouts for End-to-End Autonomous Driving
Rajeev Yasarla, Deepti Hegde, Shizhong Han +10
Vision-Language-Action (VLA) models are emerging as highly effective planning models for end-to-end autonomous driving systems. However, current works mostly rely on imitation lear…
cs.CV2025
MultiHuman-Testbench: Benchmarking Image Generation for Multiple Humans
Shubhankar Borse, Seokeon Choi, Sunghyun Park +6
Generation of images containing multiple humans, performing complex actions, while preserving their facial identities, is a significant challenge. A major factor contributing to th…
cs.CV2025
Distilling Multi-modal Large Language Models for Autonomous Driving
Deepti Hegde, Rajeev Yasarla, Hong Cai +7
Autonomous driving demands safe motion planning, especially in critical "long-tail" scenarios. Recent end-to-end autonomous driving systems leverage large language models (LLMs) as…