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

7 citations · 21 across the 15 of their papers we have counts for

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7 papers · 1 filter

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.CV2024★ 4 cited

CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation

Yue Jiang, Jiawei Chen, Dingkang Yang +5

Automatic medical report generation (MRG), which possesses significant research value as it can aid radiologists in clinical diagnosis and report composition, has garnered increasi…

cs.CV2024★ 7 cited

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

Jiawei Chen, Dingkang Yang, Tong Wu +7

Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging report generation. While these mo…

cs.CL2024★ 5 cited

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.CV2024★ 1 cited

Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models

Jiawei Chen, Dingkang Yang, Yue Jiang +4

In the realm of Medical Visual Language Models (Med-VLMs), the quest for universal efficient fine-tuning mechanisms remains paramount, especially given researchers in interdiscipli…

cs.CV2024

Can LLMs' Tuning Methods Work in Medical Multimodal Domain?

Jiawei Chen, Yue Jiang, Dingkang Yang +4

While Large Language Models (LLMs) excel in world knowledge understanding, adapting them to specific subfields requires precise adjustments. Due to the model's vast scale, traditio…

cs.CV2024★ 4 cited

MISS: A Generative Pretraining and Finetuning Approach for Med-VQA

Jiawei Chen, Dingkang Yang, Yue Jiang +2

Medical visual question answering (VQA) is a challenging multimodal task, where Vision-Language Pre-training (VLP) models can effectively improve the generalization performance. Ho…