13 citations · 24 across the 5 of their papers we have counts for
11 papers
HyperLLaVA: Dynamic Visual and Language Expert Tuning for Multimodal Large Language Models
Wenqiao Zhang, Tianwei Lin, Jiang Liu +10
Recent advancements indicate that scaling up Multimodal Large Language Models (MLLMs) effectively enhances performance on downstream multimodal tasks. The prevailing MLLM paradigm,…
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection
Jiaqi Zhu, Shaofeng Cai, Fang Deng +2
Real-time analytics and decision-making require online anomaly detection (OAD) to handle drifts in data streams efficiently and effectively. Unfortunately, existing approaches are…
Denoising Multi-modal Sequential Recommenders with Contrastive Learning
Dong Yao, Shengyu Zhang, Zhou Zhao +5
There is a rapidly-growing research interest in engaging users with multi-modal data for accurate user modeling on recommender systems. Existing multimedia recommenders have achiev…
Learning in Imperfect Environment: Multi-Label Classification with Long-Tailed Distribution and Partial Labels
Wenqiao Zhang, Changshuo Liu, Lingze Zeng +3
Conventional multi-label classification (MLC) methods assume that all samples are fully labeled and identically distributed. Unfortunately, this assumption is unrealistic in large-…
Toward Cohort Intelligence: A Universal Cohort Representation Learning Framework for Electronic Health Record Analysis
Changshuo Liu, Wenqiao Zhang, Beng Chin Ooi +3
Electronic Health Records (EHR) are generated from clinical routine care recording valuable information of broad patient populations, which provide plentiful opportunities for impr…
CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation
Wenqiao Zhang, Changshuo Liu, Can Cui +1
Semi-supervised domain adaptation (SSDA) adapts a learner to a new domain by effectively utilizing source domain data and a few labeled target samples. It is a practical yet under-…