1 citations · 1 across the 9 of their papers we have counts for
9 papers
Multimodal Prompt Learning with Irregular EHRs for Robust Monitoring of Critical Care Patients
Yixin Yang, Yueyang Sun, Weichen Liu +2
Accurate assessment of patients in intensive care units (ICUs) is essential for timely clinical intervention and improved patient outcomes. Multimodal electronic health records (EH…
Dep-LLM: Training-Free Depression Diagnosis via Evidence-Guided Structured Multi-factor with Reliable LLM Reasoning
Yiqing Lyu, Xianbing Zhao, Buzhou Tang +1
Automatic Depression Detection (ADD) from clinical interviews is a pivotal task in computational mental health, yet it remains challenging due to two critical obstacles: 1) difficu…
Towards Multimodal Sentiment Analysis via Contrastive Cross-modal Retrieval Augmentation and Hierachical Prompts
Xianbing Zhao, Shengzun Yang, Buzhou Tang +1
Multimodal sentiment analysis is a fundamental problem in the field of affective computing. Although significant progress has been made in cross-modal interaction, it remains a cha…
Physics-Grounded Motion Forecasting via Equation Discovery for Trajectory-Guided Image-to-Video Generation
Tao Feng, Xianbing Zhao, Zhenhua Chen +4
Recent advances in diffusion-based and autoregressive video generation models have achieved remarkable visual realism. However, these models typically lack accurate physical alignm…
Predicting Depression in Screening Interviews from Interactive Multi-Theme Collaboration
Xianbing Zhao, Yiqing Lyu, Di Wang +1
Automatic depression detection provides cues for early clinical intervention by clinicians. Clinical interviews for depression detection involve dialogues centered around multiple…
Learning in Order! A Sequential Strategy to Learn Invariant Features for Multimodal Sentiment Analysis
Xianbing Zhao, Lizhen Qu, Tao Feng +2
This work proposes a novel and simple sequential learning strategy to train models on videos and texts for multimodal sentiment analysis. To estimate sentiment polarities on unseen…
Toward Robust Multimodal Learning using Multimodal Foundational Models
Xianbing Zhao, Soujanya Poria, Xuejiao Li +2
Existing multimodal sentiment analysis tasks are highly rely on the assumption that the training and test sets are complete multimodal data, while this assumption can be difficult…
SHAPE: A Sample-adaptive Hierarchical Prediction Network for Medication Recommendation
Sicen Liu, Xiaolong Wang, JIngcheng Du +6
Effectively medication recommendation with complex multimorbidity conditions is a critical task in healthcare. Most existing works predicted medications based on longitudinal recor…
DKINet: Medication Recommendation via Domain Knowledge Informed Deep Learning
Sicen Liu, Xiaolong Wang, Xianbing Zhao +1
Medication recommendation is a fundamental yet crucial branch of healthcare that presents opportunities to assist physicians in making more accurate medication prescriptions for pa…