Fetching the paper…
Reading the bibliography…
Artificial intelligence has advanced in Medical Visual Question Answering (Med-VQA), but prevalent research tends to focus on the accuracy of the answers, often overlooking the reasoning paths and interpretability, which are crucial in clinical settings.
Unifiedqa: Crossing format boundaries with a single qa system
Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 1907
Earlier work this paper cites.
All you may need for vqa are image captions
Soravit Changpinyo, Doron Kukliansy, Idan Szpektor, Xi Chen, Nan Ding, and Radu Soricut. 2022 · 1963
Earlier work this paper cites.
Adaptive mixtures of local experts
Robert A Jacobs, Michael I Jordan, Steven J Nowlan, and Geoffrey E Hinton. 1991 · 1991
Earlier work this paper cites.
Pathvqa: 30000+ questions for medical visual question answering
Xuehai He, Yichen Zhang, Luntian Mou, Eric Xing, and Pengtao Xie. 2020 · 2003
Earlier work this paper cites.
Outrageously large neural networks: The sparsely-gated mixture-of-experts layer
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean. 2016 · 2016
Earlier work this paper cites.
Bilinear attention networks
Jin-Hwa Kim, Jaehyun Jun, and Byoung-Tak Zhang. 2018 · 2018
Earlier work this paper cites.
A dataset of clinically generated visual questions and answers about radiology images
Jason J Lau, Soumya Gayen, Asma Ben Abacha, and Dina Demner-Fushman. 2018 · 2018
Earlier work this paper cites.
Radiology objects in context (roco): a multimodal image dataset
Obioma Pelka, Sven Koitka, Johannes Rückert, Felix Nensa, and Christoph M Friedrich. 2018 · 2018
Earlier work this paper cites.
Vqa-med: Overview of the medical visual question answering task at imageclef 2019
Asma Ben Abacha, Sadid A Hasan, Vivek V Datla, Joey Liu, Dina Demner-Fushman, and Henning Müller. 2019 · 2019
Earlier work this paper cites.
Vqa-med: Overview of the medical visual question answering task at imageclef 2019
Asma Ben Abacha, Sadid A Hasan, Vivek V Datla, Dina Demner-Fushman, and Henning Müller. 2019 · 2019
Earlier work this paper cites.
Overcoming data limitation in medical visual question answering
Binh D Nguyen, Thanh-Toan Do, Binh X Nguyen, Tuong Do, Erman Tjiputra, and Quang D Tran. 2019 · 2019
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019 · 2019
Earlier work this paper cites.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko. 2020 · 2020
Cited alongside, same era.
Gshard: Scaling giant models with conditional computation and automatic sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, and Zhifeng Chen. 2020 · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
Cited alongside, same era.
Cgmvqa: A new classification and generative model for medical visual question answering
Fuji Ren and Yangyang Zhou. 2020 · 2020
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2020 · 2020
Cited alongside, same era.
Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
Later among the works it cites.
Clip models are few-shot learners: Empirical studies on vqa and visual entailment
Haoyu Song, Li Dong, Weinan Zhang, Ting Liu, and Furu Wei. 2022 · 2022
Later among the works it cites.
Plug-and-play VQA: Zero-shot VQA by conjoining large pretrained models with zero training
Anthony Meng Huat Tiong, Junnan Li, Boyang Li, Silvio Savarese, and Steven C.H. Hoi. 2022a · 2022
Later among the works it cites.
Plug-and-play VQA: Zero-shot VQA by conjoining large pretrained models with zero training
Anthony Meng Huat Tiong, Junnan Li, Boyang Li, Silvio Savarese, and Steven C.H. Hoi. 2022b · 2022
Later among the works it cites.
Clip-td: Clip targeted distillation for vision-language tasks
Zhecan Wang, Bin Xiao, Noel Codella, Jianwei Yang, Yen-Chun Chen, Luowei Zhou, Shih-Fu Chang, Xiyang Dai, Haoxuan You, and Lu Yuan. 2022 · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Medical visual question answering via conditional reasoning
Li-Ming Zhan, Bo Liu, Lu Fan, Jiaxin Chen, and Xiao-Ming Wu. 2020 · 2020
Cited alongside, same era.
Weaqa: Weak supervision via captions for visual question answering
Pratyay Banerjee, Tejas Gokhale, Yezhou Yang, and Chitta Baral. 2021 · 2021
Cited alongside, same era.
Sedigheh Eslami, Gerard de Melo, and Christoph Meinel. 2021 · 2021
Cited alongside, same era.
Cross-modal self-attention with multi-task pre-training for medical visual question answering
Haifan Gong, Guanqi Chen, Sishuo Liu, Yizhou Yu, and Guanbin Li. 2021 · 2021
Cited alongside, same era.
Mmbert: multimodal bert pretraining for improved medical vqa
Yash Khare, Viraj Bagal, Minesh Mathew, Adithi Devi, U Deva Priyakumar, and CV Jawahar. 2021 · 2021
Cited alongside, same era.
Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering
Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, and Xiao-Ming Wu. 2021 · 2021
Cited alongside, same era.
Align, reason and learn: Enhancing medical vision-and-language pre-training with knowledge
Zhihong Chen, Guanbin Li, and Xiang Wan. 2022 · 2022
Cited alongside, same era.
PubMedCLIP: How much does CLIP benefit visual question answering in the medical domain?
Sedigheh Eslami, Christoph Meinel, and Gerard de Melo. 2023 · 2023
Later among the works it cites.
Chameleon: Plug-and-play compositional reasoning with large language models
Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, and Jianfeng Gao. 2023 · 2023
Later among the works it cites.
Ddcot: Duty-distinct chain-of-thought prompting for multimodal reasoning in language models
Ge Zheng, Bin Yang, Jiajin Tang, Hong-Yu Zhou, and Sibei Yang. 2023 · 2023
Later among the works it cites.
Medthink: Explaining medical visual question answering via multimodal decision-making rationale
Xiaotang Gai, Chenyi Zhou, Jiaxiang Liu, Yang Feng, Jian Wu, and Zuozhu Liu. 2024 · 2024
Closest in time.
Llava-med: Training a large language-and-vision assistant for biomedicine in one day
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, and Jianfeng Gao. 2024 · 2024
Closest in time.
Scalable geometric fracture assembly via co-creation space among assemblers
Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, and Chao Wu. 2024 · 2024
Closest in time.