1 citations · 2 across the 6 of their papers we have counts for
6 papers
Graph-Supervised Hierarchical Clinical Alignment for Radiology Report Generation with Large Language Models
Yingshu Li, Yunyi Liu, Zhanyu Wang +4
Radiology report generation (RRG) has recently benefited from large language models, which substantially improve report fluency. However, clinically faithful generation remains cha…
S-RRG-Bench: Structured Radiology Report Generation with Fine-Grained Evaluation Framework
Yingshu Li, Yunyi Liu, Zhanyu Wang +4
Radiology report generation (RRG) for diagnostic images, such as chest X-rays, plays a pivotal role in both clinical practice and AI. Traditional free-text reports suffer from redu…
ReFINE: A Reward-Based Framework for Interpretable and Nuanced Evaluation of Radiology Report Generation
Yunyi Liu, Yingshu Li, Zhanyu Wang +4
Automated radiology report generation (R2Gen) has advanced significantly, introducing challenges in accurate evaluation due to its complexity. Traditional metrics often fall short…
KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models
Yingshu Li, Zhanyu Wang, Yunyi Liu +3
Harnessing the robust capabilities of Large Language Models (LLMs) for narrative generation, logical reasoning, and common-sense knowledge integration, this study delves into utili…
Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models
Bingshuai Liu, Chenyang Lyu, Zijun Min +3
The advancement of Large Language Models (LLMs) has brought substantial attention to the Chain of Thought (CoT) approach, primarily due to its ability to enhance the capability of…
GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation
Zhanyu Wang, Longyue Wang, Zhen Zhao +7
While the recent advances in Multimodal Large Language Models (MLLMs) constitute a significant leap forward in the field, these models are predominantly confined to the realm of in…