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Generating accurate radiology reports from medical images is a clinically important but challenging task.
Selective classification for deep neural networks
Yonatan Geifman and Ran El-Yaniv · 2017
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Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports
Alistair EW Johnson, Tom J Pollard, Seth J Berkowitz, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Roger G Mark, and Steven Horng · 2019
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Quantifying and leveraging predictive uncertainty for medical image assessment
Florin C Ghesu, Bogdan Georgescu, Awais Mansoor, Youngjin Yoo, Eli Gibson, RS Vishwanath, Abishek Balachandran, James M Balter, Yue Cao, Ramandeep Singh, et al · 2021
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Radgraph: Extracting clinical entities and relations from radiology reports
Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven QH Truong, Du Nguyen Duong, Tan Bui, Pierre Chambon, Yuhao Zhang, Matthew P Lungren, Andrew Y Ng, et al · 2021
Earlier work this paper cites.
The art of abstention: Selective prediction and error regularization for natural language processing
Ji Xin, Raphael Tang, Yaoliang Yu, and Jimmy Lin · 2021
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Improving radiology report generation systems by removing hallucinated references to non-existent priors
Vignav Ramesh, Nathan A Chi, and Pranav Rajpurkar · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Anastasios N. Angelopoulos, Stephen Bates, Adam Fisch, Lihua Lei, and Tal Schuster · 2023
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Yuheng Huang, Jiayang Song, Zhijie Wang, Shengming Zhao, Huaming Chen, Felix Juefei-Xu, and Lei Ma · 2023
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SelfCheckGPT: Zero-resource black-box hallucination detection for generative large language models
Potsawee Manakul, Adian Liusie, and Mark Gales · 2023
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Chantal Pellegrini, Ege Özsoy, Benjamin Busam, Nassir Navab, and Matthias Keicher · 2023
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Interactive and explainable region-guided radiology report generation
Tim Tanida, Philip Müller, Georgios Kaissis, and Daniel Rueckert · 2023
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Hybrid uncertainty quantification for selective text classification in ambiguous tasks
Artem Vazhentsev, Gleb Kuzmin, Akim Tsvigun, Alexander Panchenko, Maxim Panov, Mikhail Burtsev, and Artem Shelmanov · 2023
Cited alongside, same era.
Evaluating progress in automatic chest x-ray radiology report generation
Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Min Ho Lee, Zahra Shakeri Hossein Abad, Andrew Y Ng, et al · 2023
Chexagent: Towards a foundation model for chest x-ray interpretation, 2024
Zhihong Chen, Maya Varma, Jean-Benoit Delbrouck, Magdalini Paschali, Louis Blankemeier, Dave Van Veen, Jeya Maria Jose Valanarasu, Alaa Youssef, Joseph Paul Cohen, Eduardo Pontes Reis, Emily B. Tsai, Andrew Johnston, Cameron Olsen, Tanishq Mathew Abraham, Sergios Gatidis, Akshay S. Chaudhari, and Curtis Langlotz · 2024
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Detecting hallucinations in large language models using semantic entropy
Sebastian Farquhar, Jannik Kossen, Lorenz Kuhn, and Yarin Gal · 2024
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Rajpurkar Lab · 2024
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Niels Mündler, Jingxuan He, Slobodan Jenko, and Martin Vechev · 2024
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Trust it or not: Confidence-guided automatic radiology report generation
Yixin Wang, Zihao Lin, Zhe Xu, Haoyu Dong, Jie Luo, Jiang Tian, Zhongchao Shi, Lifu Huang, Yang Zhang, Jianping Fan, et al · 2024
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Cited alongside, same era.
Hallucination mitigating for medical report generation
Anonymous · 2024
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Hallucination of multimodal large language models: A survey, 2024
Zechen Bai, Pichao Wang, Tianjun Xiao, Tong He, Zongbo Han, Zheng Zhang, and Mike Zheng Shou · 2024
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Oishi Banerjee, Hong-Yu Zhou, Subathra Adithan, Stephen Kwak, Kay Wu, and Pranav Rajpurkar · 2024
Cited alongside, same era.
Maira-2: Grounded radiology report generation, 2024
Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P. Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, and Stephanie L. Hyland · 2024
Cited alongside, same era.
A survey on hallucination in large vision-language models, 2024a
Hanchao Liu, Wenyuan Xue, Yifei Chen, Dapeng Chen, Xiutian Zhao, Ke Wang, Liping Hou, Rongjun Li, and Wei Peng
Cited in the paper.
Uncertainty estimation and quantification for llms: A simple supervised approach, 2024b
Linyu Liu, Yu Pan, Xiaocheng Li, and Guanting Chen
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Mitigating llm hallucinations via conformal abstention, 2024
Yasin Abbasi Yadkori, Ilja Kuzborskij, David Stutz, András György, Adam Fisch, Arnaud Doucet, Iuliya Beloshapka, Wei-Hung Weng, Yao-Yuan Yang, Csaba Szepesvári, Ali Taylan Cemgil, and Nenad Tomasev · 2024
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Luq: Long-text uncertainty quantification for llms, 2024
Caiqi Zhang, Fangyu Liu, Marco Basaldella, and Nigel Collier · 2024
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A generalist learner for multifaceted medical image interpretation, 2024
Hong-Yu Zhou, Subathra Adithan, Julián Nicolás Acosta, Eric J. Topol, and Pranav Rajpurkar · 2024
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