9 papers
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 +9
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…