\begin{thebibliography}{28}
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\bibitem[Ahmed et~al.(2024)Ahmed, Sellergren, Yang, Xu, Babenko, Ward, Olson, Mohtashamian, Matias, Corrado, et~al.]{ahmedPathAlignVisionlanguageModel2024}
Faruk Ahmed, Andrew Sellergren, Lin Yang, Shawn Xu, Boris Babenko, Abbi Ward, Niels Olson, Arash Mohtashamian, Yossi Matias, Greg~S Corrado, et~al.
\newblock Pathalign: A vision-language model for whole slide images in histopathology.
\newblock \emph{arXiv preprint arXiv:2406.19578}, 2024.

\bibitem[B{\'a}ndi et~al.(2023)B{\'a}ndi, Balkenhol, Van~Dijk, Kok, van Ginneken, van~der Laak, and Litjens]{bandiContinualLearningStrategies2023}
P{\'e}ter B{\'a}ndi, Maschenka Balkenhol, Marcory Van~Dijk, Michel Kok, Bram van Ginneken, Jeroen van~der Laak, and Geert Litjens.
\newblock Continual learning strategies for cancer-independent detection of lymph node metastases.
\newblock \emph{Medical Image Analysis}, 85:\penalty0 102755, 2023.

\bibitem[Bosma et~al.(2025)Bosma, Dercksen, Builtjes, Andr{\'e}, Roest, Fransen, Noordman, Navarro-Padilla, Lefkes, Alves, et~al.]{joeranbosmaDragonrobertabasedomainspecific2024}
Joeran~S Bosma, Koen Dercksen, Luc Builtjes, Romain Andr{\'e}, Christian Roest, Stefan~J Fransen, Constant~R Noordman, Mar Navarro-Padilla, Judith Lefkes, Nat{\'a}lia Alves, et~al.
\newblock The dragon benchmark for clinical nlp.
\newblock \emph{npj Digital Medicine}, 8\penalty0 (1):\penalty0 1--10, 2025.

\bibitem[Bulten et~al.(2022)Bulten, Kartasalo, Chen, Str{\"o}m, Pinckaers, Nagpal, Cai, Steiner, Van~Boven, Vink, et~al.]{bultenArtificialIntelligenceDiagnosis2022}
Wouter Bulten, Kimmo Kartasalo, Po-Hsuan~Cameron Chen, Peter Str{\"o}m, Hans Pinckaers, Kunal Nagpal, Yuannan Cai, David~F Steiner, Hester Van~Boven, Robert Vink, et~al.
\newblock Artificial intelligence for diagnosis and gleason grading of prostate cancer: the panda challenge.
\newblock \emph{Nature medicine}, 28\penalty0 (1):\penalty0 154--163, 2022.

\bibitem[Chen et~al.(2024)Chen, Ding, Lu, Williamson, Jaume, Song, Chen, Zhang, Shao, Shaban, et~al.]{chenGeneralpurposeFoundationModel2024b}
Richard~J Chen, Tong Ding, Ming~Y Lu, Drew~FK Williamson, Guillaume Jaume, Andrew~H Song, Bowen Chen, Andrew Zhang, Daniel Shao, Muhammad Shaban, et~al.
\newblock Towards a general-purpose foundation model for computational pathology.
\newblock \emph{Nature Medicine}, 30\penalty0 (3):\penalty0 850--862, 2024.

\bibitem[Grisi et~al.(2023)Grisi, Litjens, and van~der Laak]{grisiHierarchicalVisionTransformers2023}
Cl{\'e}ment Grisi, Geert Litjens, and Jeroen van~der Laak.
\newblock Hierarchical vision transformers for context-aware prostate cancer grading in whole slide images.
\newblock \emph{arXiv preprint arXiv:2312.12619}, 2023.

\bibitem[Ikezogwo et~al.(2023)Ikezogwo, Seyfioglu, Ghezloo, Geva, Sheikh~Mohammed, Anand, Krishna, and Shapiro]{ikezogwoQuilt1MOneMillion2023}
Wisdom Ikezogwo, Saygin Seyfioglu, Fatemeh Ghezloo, Dylan Geva, Fatwir Sheikh~Mohammed, Pavan~Kumar Anand, Ranjay Krishna, and Linda Shapiro.
\newblock Quilt-1m: One million image-text pairs for histopathology.
\newblock \emph{Advances in neural information processing systems}, 36:\penalty0 37995--38017, 2023.

\bibitem[Karamcheti et~al.(2024)Karamcheti, Nair, Balakrishna, Liang, Kollar, and Sadigh]{karamchetiPrismaticVLMsInvestigating2024a}
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, and Dorsa Sadigh.
\newblock Prismatic vlms: Investigating the design space of visually-conditioned language models.
\newblock In \emph{Forty-first International Conference on Machine Learning}, 2024.

\bibitem[Kirkpatrick et~al.(2017)Kirkpatrick, Pascanu, Rabinowitz, Veness, Desjardins, Rusu, Milan, Quan, Ramalho, Grabska-Barwinska, et~al.]{kirkpatrickOvercomingCatastrophicForgetting2017}
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei~A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et~al.
\newblock Overcoming catastrophic forgetting in neural networks.
\newblock \emph{Proceedings of the national academy of sciences}, 114\penalty0 (13):\penalty0 3521--3526, 2017.

\bibitem[Lauren{\c{c}}on et~al.(2024)Lauren{\c{c}}on, Tronchon, Cord, and Sanh]{laurenconWhatMattersWhen2024}
Hugo Lauren{\c{c}}on, L{\'e}o Tronchon, Matthieu Cord, and Victor Sanh.
\newblock What matters when building vision-language models?
\newblock \emph{Advances in Neural Information Processing Systems}, 37:\penalty0 87874--87907, 2024.

\bibitem[Lee et~al.(2020)Lee, Yoon, Kim, Kim, Kim, So, and Kang]{leeBioBERTPretrainedBiomedical2020}
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan~Ho So, and Jaewoo Kang.
\newblock Biobert: a pre-trained biomedical language representation model for biomedical text mining.
\newblock \emph{Bioinformatics}, 36\penalty0 (4):\penalty0 1234--1240, 2020.

\bibitem[Lin et~al.(2014)Lin, Maire, Belongie, Hays, Perona, Ramanan, Doll{\'a}r, and Zitnick]{linMicrosoftCOCOCommon2015}
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll{\'a}r, and C~Lawrence Zitnick.
\newblock Microsoft coco: Common objects in context.
\newblock In \emph{Computer vision--ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part v 13}, pages 740--755. Springer, 2014.

\bibitem[Lu et~al.(2024)Lu, Chen, Williamson, Chen, Liang, Ding, Jaume, Odintsov, Le, Gerber, et~al.]{luVisualLanguageFoundationModel2023}
Ming~Y Lu, Bowen Chen, Drew~FK Williamson, Richard~J Chen, Ivy Liang, Tong Ding, Guillaume Jaume, Igor Odintsov, Long~Phi Le, Georg Gerber, et~al.
\newblock A visual-language foundation model for computational pathology.
\newblock \emph{Nature Medicine}, 30\penalty0 (3):\penalty0 863--874, 2024.

\bibitem[Perkonigg et~al.(2021)Perkonigg, Hofmanninger, Herold, Brink, Pianykh, Prosch, and Langs]{perkoniggDynamicMemoryAlleviate2021}
Matthias Perkonigg, Johannes Hofmanninger, Christian~J Herold, James~A Brink, Oleg Pianykh, Helmut Prosch, and Georg Langs.
\newblock Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging.
\newblock \emph{Nature communications}, 12\penalty0 (1):\penalty0 5678, 2021.

\bibitem[Radford et~al.(2021)Radford, Kim, Hallacy, Ramesh, Goh, Agarwal, Sastry, Askell, Mishkin, Clark, et~al.]{radfordLearningTransferableVisual2021b}
Alec Radford, Jong~Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et~al.
\newblock Learning transferable visual models from natural language supervision.
\newblock In \emph{International conference on machine learning}, pages 8748--8763. PmLR, 2021.

\bibitem[Rebuffi et~al.(2017)Rebuffi, Kolesnikov, Sperl, and Lampert]{rebuffiICaRLIncrementalClassifier2017}
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph~H Lampert.
\newblock icarl: Incremental classifier and representation learning.
\newblock In \emph{Proceedings of the IEEE conference on Computer Vision and Pattern Recognition}, pages 2001--2010, 2017.

\bibitem[Reimers and Gurevych(2019)]{reimersSentenceBERTSentenceEmbeddings2019a}
Nils Reimers and Iryna Gurevych.
\newblock Sentence-bert: Sentence embeddings using siamese bert-networks.
\newblock \emph{arXiv preprint arXiv:1908.10084}, 2019.

\bibitem[Rusu et~al.(2016)Rusu, Rabinowitz, Desjardins, Soyer, Kirkpatrick, Kavukcuoglu, Pascanu, and Hadsell]{rusuProgressiveNeuralNetworks2022}
Andrei~A Rusu, Neil~C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell.
\newblock Progressive neural networks.
\newblock \emph{arXiv preprint arXiv:1606.04671}, 2016.

\bibitem[Schroff et~al.(2015)Schroff, Kalenichenko, and Philbin]{schroffFaceNetUnifiedEmbedding2015}
Florian Schroff, Dmitry Kalenichenko, and James Philbin.
\newblock Facenet: A unified embedding for face recognition and clustering.
\newblock In \emph{Proceedings of the IEEE conference on computer vision and pattern recognition}, pages 815--823, 2015.

\bibitem[Shaikovski et~al.(2024)Shaikovski, Casson, Severson, Zimmermann, Wang, Kunz, Retamero, Oakley, Klimstra, Kanan, et~al.]{shaikovskiPRISMMultiModalGenerative2024}
George Shaikovski, Adam Casson, Kristen Severson, Eric Zimmermann, Yi~Kan Wang, Jeremy~D Kunz, Juan~A Retamero, Gerard Oakley, David Klimstra, Christopher Kanan, et~al.
\newblock Prism: A multi-modal generative foundation model for slide-level histopathology.
\newblock \emph{arXiv preprint arXiv:2405.10254}, 2024.

\bibitem[Tong et~al.(2024)Tong, Liu, Zhai, Ma, LeCun, and Xie]{tongEyesWideShut2024}
Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi~Ma, Yann LeCun, and Saining Xie.
\newblock Eyes wide shut? exploring the visual shortcomings of multimodal llms.
\newblock In \emph{Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages 9568--9578, 2024.

\bibitem[Tran et~al.(2024)Tran, Schmidle, Wagner, Koch, Lupperger, Feuchtinger, B{\"o}hner, Kaczmarczyk, Biedermann, Eyerich, et~al.]{tran2024generating}
Manuel Tran, Paul Schmidle, Sophia~J Wagner, Valentin Koch, Valerio Lupperger, Annette Feuchtinger, Alexander B{\"o}hner, Robert Kaczmarczyk, Tilo Biedermann, Kilian Eyerich, et~al.
\newblock Generating highly accurate pathology reports from gigapixel whole slide images with histogpt.
\newblock \emph{medRxiv}, pages 2024--03, 2024.

\bibitem[Vorontsov et~al.(2023)Vorontsov, Bozkurt, Casson, Shaikovski, Zelechowski, Liu, Severson, Zimmermann, Hall, Tenenholtz, et~al.]{vorontsovVirchowMillionSlideDigital2024}
Eugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski, Siqi Liu, Kristen Severson, Eric Zimmermann, James Hall, Neil Tenenholtz, et~al.
\newblock Virchow: A million-slide digital pathology foundation model.
\newblock \emph{arXiv preprint arXiv:2309.07778}, 2023.

\bibitem[Wang et~al.(2024)Wang, Zhao, Marostica, Yuan, Jin, Zhang, Li, Tang, Wang, Li, et~al.]{wangPathologyFoundationModel2024a}
Xiyue Wang, Junhan Zhao, Eliana Marostica, Wei Yuan, Jietian Jin, Jiayu Zhang, Ruijiang Li, Hongping Tang, Kanran Wang, Yu~Li, et~al.
\newblock A pathology foundation model for cancer diagnosis and prognosis prediction.
\newblock \emph{Nature}, 634\penalty0 (8035):\penalty0 970--978, 2024.

\bibitem[Wu et~al.(2020)Wu, Xu, Dai, Wan, Zhang, Yan, Tomizuka, Gonzalez, Keutzer, and Vajda]{wuVisualTransformersTokenbased2020}
Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Zhicheng Yan, Masayoshi Tomizuka, Joseph Gonzalez, Kurt Keutzer, and Peter Vajda.
\newblock Visual transformers: Token-based image representation and processing for computer vision.
\newblock \emph{arXiv preprint arXiv:2006.03677}, 2020.

\bibitem[Zhai et~al.(2023)Zhai, Tong, Li, Cai, Qu, Lee, and Ma]{zhaiInvestigatingCatastrophicForgetting2023}
Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu~Cai, Qing Qu, Yong~Jae Lee, and Yi~Ma.
\newblock Investigating the catastrophic forgetting in multimodal large language models.
\newblock \emph{arXiv preprint arXiv:2309.10313}, 2023.

\bibitem[Zhang et~al.(2022)Zhang, Jiang, Miura, Manning, and Langlotz]{zhangContrastiveLearningMedical2022a}
Yuhao Zhang, Hang Jiang, Yasuhide Miura, Christopher~D Manning, and Curtis~P Langlotz.
\newblock Contrastive learning of medical visual representations from paired images and text.
\newblock In \emph{Machine learning for healthcare conference}, pages 2--25. PMLR, 2022.

\bibitem[Zhang et~al.(2024)Zhang, Unell, Wang, Ghosh, Su, Schmidt, and Yeung-Levy]{zhangWhyAreVisuallyGrounded2024a}
Yuhui Zhang, Alyssa Unell, Xiaohan Wang, Dhruba Ghosh, Yuchang Su, Ludwig Schmidt, and Serena Yeung-Levy.
\newblock Why are visually-grounded language models bad at image classification?
\newblock \emph{arXiv preprint arXiv:2405.18415}, 2024.

\end{thebibliography}
