7 citations · 31 across the 40 of their papers we have counts for
5 papers · 1 filter
Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning
Mingcheng Li, Dingkang Yang, Yang Liu +11
Multimodal Sentiment Analysis (MSA) is an important research area that aims to understand and recognize human sentiment through multiple modalities. The complementary information p…
MedAide: Information Fusion and Anatomy of Medical Intents via LLM-based Agent Collaboration
Dingkang Yang, Jinjie Wei, Mingcheng Li +8
In healthcare intelligence, the ability to fuse heterogeneous, multi-intent information from diverse clinical sources is fundamental to building reliable decision-making systems. L…
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators
Dingkang Yang, Dongling Xiao, Jinjie Wei +4
Despite their remarkable capabilities, Large Language Models (LLMs) are prone to generate responses that contradict verifiable facts, i.e., unfaithful hallucination content. Existi…
PediatricsGPT: Large Language Models as Chinese Medical Assistants for Pediatric Applications
Dingkang Yang, Jinjie Wei, Dongling Xiao +11
Developing intelligent pediatric consultation systems offers promising prospects for improving diagnostic efficiency, especially in China, where healthcare resources are scarce. De…
Towards Multimodal Sentiment Analysis Debiasing via Bias Purification
Dingkang Yang, Mingcheng Li, Dongling Xiao +7
Multimodal Sentiment Analysis (MSA) aims to understand human intentions by integrating emotion-related clues from diverse modalities, such as visual, language, and audio. Unfortuna…