5 citations · 5 across the 4 of their papers we have counts for
4 papers
Wearable-informed generative digital avatars predict task-conditioned post-stroke locomotion
Yanning Dai, Chenyu Tang, Ruizhi Zhang +16
Dynamic prediction of locomotor capacity after stroke could enable more individualized rehabilitation, yet current assessments largely provide static impairment scores and do not i…
IF-VidCap: Can Video Caption Models Follow Instructions?
Shihao Li, Yuanxing Zhang, Jiangtao Wu +20
Although Multimodal Large Language Models (MLLMs) have demonstrated proficiency in video captioning, practical applications require captions that follow specific user instructions…
Self-signals Driven Multi-LLM Debate for Efficient and Accurate Reasoning
Xuhang Chen, Zhifan Song, Deyi Ji +2
Large Language Models (LLMs) have exhibited impressive capabilities across diverse application domains. Recent work has explored Multi-LLM Agent Debate (MAD) as a way to enhance pe…
An AI-Driven Multimodal Smart Home Platform for Continuous Monitoring and Assistance in Post-Stroke Motor Impairment
Chenyu Tang, Ruizhi Zhang, Shuo Gao +21
At-home rehabilitation for post-stroke patients presents significant challenges, as continuous, personalized care is often limited outside clinical settings. Moreover, the lack of…