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20242026
most citedGREEN: Generative Radiology Report Evaluation and Error Notation

42 citations · 77 across the 15 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

Symbal: Detecting Systematic Misalignments in Model-Generated Captions

Maya Varma, Jean-Benoit Delbrouck, Sophie Ostmeier +2

Multimodal large language models (MLLMs) often introduce errors when generating image captions, resulting in misaligned image-text pairs. Our work focuses on a class of captioning…

cs.CV2026

CheXTemporal: A Dataset for Temporally-Grounded Reasoning in Chest Radiography

Eva Prakash, Yunhe Gao, Chong Wang +10

Chest radiograph interpretation requires temporal reasoning over prior and current studies, yet most vision-language models are trained on static image-report pairs and lack explic…

cs.CV2026

A Reasoning-Enabled Vision-Language Foundation Model for Chest X-ray Interpretation

Yabin Zhang, Chong Wang, Yunhe Gao +19

Chest X-rays (CXRs) are among the most frequently performed imaging examinations worldwide, yet rising imaging volumes increase radiologist workload and the risk of diagnostic erro…

cs.CV2025

TRoVe: Discovering Error-Inducing Static Feature Biases in Temporal Vision-Language Models

Maya Varma, Jean-Benoit Delbrouck, Sophie Ostmeier +2

Vision-language models (VLMs) have made great strides in addressing temporal understanding tasks, which involve characterizing visual changes across a sequence of images. However,…

cs.CV2025

From Detection to Mitigation: Addressing Bias in Deep Learning Models for Chest X-Ray Diagnosis

Clemence Mottez, Louisa Fay, Maya Varma +2

Deep learning models have shown promise in improving diagnostic accuracy from chest X-rays, but they also risk perpetuating healthcare disparities when performance varies across de…

cs.CV2024★ 1 cited

CheXalign: Preference fine-tuning in chest X-ray interpretation models without human feedback

Dennis Hein, Zhihong Chen, Sophie Ostmeier +8

Radiologists play a crucial role in translating medical images into actionable reports. However, the field faces staffing shortages and increasing workloads. While automated approa…

cs.CV2024

LieRE: Lie Rotational Positional Encodings

Sophie Ostmeier, Brian Axelrod, Maya Varma +3

Transformer architectures rely on position encodings to model the spatial structure of input data. Rotary Position Encoding (RoPE) is a widely used method in language models that e…

cs.CV2024★ 33 cited

Merlin: A Computed Tomography Vision-Language Foundation Model and Dataset

Louis Blankemeier, Ashwin Kumar, Joseph Paul Cohen +37

The large volume of abdominal computed tomography (CT) scans coupled with the shortage of radiologists have intensified the need for automated medical image analysis tools. Previou…