5 citations · 8 across the 8 of their papers we have counts for
10 papers
Deformations of Holomorphic -Contact Structures
Dan Popovici
We investigate the notion of holomorphic -contact structure, that we introduced recently in the scalar case with H. Kasuya and L. Ugarte and in the line-bundle case with K. Brod…
CCS: Clinical Consensus Selection for Radiology Report Generation
Xi Zhang, Yingshu Li, Zaiqiao Meng +2
Radiology report generation (RRG) is commonly formulated as a single-path generation task, where a multimodal large language model (MLLM) produces one decoded report as the final o…
EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery
Yougang Lyu, Xi Zhang, Xinhao Yi +11
The increasing adoption of Large Language Models (LLMs) has enabled AI scientists to perform complex end-to-end scientific discovery tasks requiring coordination of specialized rol…
CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decoding
Xi Zhang, Zaiqiao Meng, Jake Lever +1
Multimodal large language models (MLLMs) have recently achieved remarkable progress in radiology by integrating visual perception with natural language understanding. However, they…
RadEval: A framework for radiology text evaluation
Justin Xu, Xi Zhang, Javid Abderezaei +9
We introduce RadEval, a unified, open-source framework for evaluating radiology texts. RadEval consolidates a diverse range of metrics, from classic n-gram overlap (BLEU, ROUGE) an…
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
Jinyuan Fang, Yanwen Peng, Xi Zhang +12
Recent advances in large language models have sparked growing interest in AI agents capable of solving complex, real-world tasks. However, most existing agent systems rely on manua…
Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reports
Francesco Dalla Serra, Patrick Schrempf, Chaoyang Wang +3
We present a novel approach to Chest X-ray (CXR) Visual Question Answering (VQA), addressing both single-image image-difference questions. Single-image questions focus on abnormali…
Can We Edit LLMs for Long-Tail Biomedical Knowledge?
Xinhao Yi, Jake Lever, Kevin Bryson +1
Knowledge editing has emerged as an effective approach for updating large language models (LLMs) by modifying their internal knowledge. However, their application to the biomedical…
Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation
Xi Zhang, Zaiqiao Meng, Jake Lever +1
We introduce a radiology-focused visual language model designed to generate radiology reports from chest X-rays. Building on previous findings that large language models (LLMs) can…
Libra: Leveraging Temporal Images for Biomedical Radiology Analysis
Xi Zhang, Zaiqiao Meng, Jake Lever +1
Radiology report generation (RRG) requires advanced medical image analysis, effective temporal reasoning, and accurate text generation. While multimodal large language models (MLLM…