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20232026
most citedTowards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge

44 citations · 71 across the 14 of their papers we have counts for

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cs.CV2026

MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation

Yi Lin, Yihao Ding, Elana Benishay +8

Automated chest CT report generation remains challenging because clinically faithful reporting requires both whole-volume understanding and accurate description of localized anatom…

cs.AI2026

Reinforcement Learning Improves LLM Accuracy and Reasoning in Disease Classification from Radiology Reports

Yishu Wei, Yi Lin, Adam Flanders +2

Accurate disease classification from radiology reports is essential for many applications. While supervised fine-tuning (SFT) of lightweight LLMs improves accuracy, it can degrade…

cs.CV2026

CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification

Hexin Dong, Yi Lin, Pengyu Zhou +25

Chest X-ray (CXR) interpretation is hindered by the long-tailed distribution of pathologies and the open-world nature of clinical environments. Existing benchmarks often rely on cl…

cs.CV2026

Overview of the CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification

Hexin Dong, Yi Lin, Pengyu Zhou +7

Chest X-ray (CXR) interpretation is hindered by the long-tailed distribution of pathologies and the open-world nature of clinical environments. Existing benchmarks often rely on cl…

cs.CL2026

RSNA Large Language Model Benchmark Dataset for Chest Radiographs of Cardiothoracic Disease: Radiologist Evaluation and Validation Enhanced by AI Labels (REVEAL-CXR)

Yishu Wei, Adam E. Flanders, Errol Colak +35

Multimodal large language models have demonstrated comparable performance to that of radiology trainees on multiple-choice board-style exams. However, to develop clinically useful…