4 papers · 1 filter
Wolf: Dense Video Captioning with a World Summarization Framework
Boyi Li, Ligeng Zhu, Ran Tian +20
We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is an automated captioning framework that adopts a mixture-of-experts approach, leveraging comp…
Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models
Zhejun Zhang, Peter Karkus, Maximilian Igl +4
Traffic simulation aims to learn a policy for traffic agents that, when unrolled in closed-loop, faithfully recovers the joint distribution of trajectories observed in the real wor…
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
Can Jin, Tong Che, Hongwu Peng +3
Generalization remains a central challenge in machine learning. In this work, we propose Learning from Teaching (LoT), a novel regularization technique for deep neural networks to…
RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios
Wenhao Ding, Yulong Cao, Ding Zhao +2
Simulation plays a crucial role in the development of autonomous vehicles (AVs) due to the potential risks associated with real-world testing. Although significant progress has bee…