2 citations · 6 across the 14 of their papers we have counts for
5 papers · 1 filter
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting
Chunlin Tian, Li Li, Kahou Tam +2
Federated Learning (FL) enables multiple devices to collaboratively train a shared model while preserving data privacy. Ever-increasing model complexity coupled with limited memory…
When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models
Haicheng Liao, Yongkang Li, Chengyue Wang +6
As autonomous driving systems increasingly become part of daily transportation, the ability to accurately anticipate and mitigate potential traffic accidents is paramount. Traditio…
CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions
Haicheng Liao, Haoyu Sun, Huanming Shen +6
Accurately and promptly predicting accidents among surrounding traffic agents from camera footage is crucial for the safety of autonomous vehicles (AVs). This task presents substan…
Towards Federated Domain Unlearning: Verification Methodologies and Challenges
Kahou Tam, Kewei Xu, Li Li +1
Federated Learning (FL) has evolved as a powerful tool for collaborative model training across multiple entities, ensuring data privacy in sensitive sectors such as healthcare and…
Characterized Diffusion and Spatial-Temporal Interaction Network for Trajectory Prediction in Autonomous Driving
Haicheng Liao, Xuelin Li, Yongkang Li +7
Trajectory prediction is a cornerstone in autonomous driving (AD), playing a critical role in enabling vehicles to navigate safely and efficiently in dynamic environments. To addre…