1 citations · 1 across the 4 of their papers we have counts for
5 papers
AcupunctureBench: A Multimodal Benchmark for Evaluating Generative Models in the Acupuncture Domain
Shusheng Li, Yifei Qu, Zichen Han +12
As large language models (LLMs) are increasingly applied in the field of traditional Chinese medicine (TCM), standardized benchmark evaluations for TCM have gradually emerged. Acup…
UV-M3TL: A Unified and Versatile Multimodal Multi-Task Learning Framework for Assistive Driving Perception
Wenzhuo Liu, Qiannan Guo, Zhen Wang +9
Advanced Driver Assistance Systems (ADAS) need to understand human driver behavior while perceiving their navigation context, but jointly learning these heterogeneous tasks would c…
CrossRay3D: Geometry and Distribution Guidance for Efficient Multimodal 3D Detection
Huiming Yang, Wenzhuo Liu, Yicheng Qiao +8
The sparse cross-modality detector offers more advantages than its counterpart, the Bird's-Eye-View (BEV) detector, particularly in terms of adaptability for downstream tasks and c…
TEM^3-Learning: Time-Efficient Multimodal Multi-Task Learning for Advanced Assistive Driving
Wenzhuo Liu, Yicheng Qiao, Zhen Wang +8
Multi-task learning (MTL) can advance assistive driving by exploring inter-task correlations through shared representations. However, existing methods face two critical limitations…
MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception
Wenzhuo Liu, Wenshuo Wang, Yicheng Qiao +9
Advanced driver assistance systems require a comprehensive understanding of the driver's mental/physical state and traffic context but existing works often neglect the potential be…