activity
20242026
most citedDetecting and Evaluating Medical Hallucinations in Large Vision Language Models

7 citations · 8 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…