Fetching the paper…
Reading the bibliography…
Multimodal Large Language Models (MLLMs) have tremendous potential to improve the accuracy, availability, and cost-effectiveness of healthcare by providing automated solutions or serving as aids to medical professionals.
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
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
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
Earlier work this paper cites.
Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano · 2020
Earlier work this paper cites.
Overview of the vqa-med task at imageclef 2021: Visual question answering and generation in the medical domain
Asma Ben Abacha, Mourad Sarrouti, Dina Demner-Fushman, Sadid A Hasan, and Henning Müller · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
Earlier work this paper cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Earlier work this paper cites.
Winoground: Probing vision and language models for visio-linguistic compositionality
Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross · 2022
Earlier work this paper cites.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou · 2022
Earlier work this paper cites.
Reproducible scaling laws for contrastive language-image learning
Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev · 2023
Earlier work this paper cites.
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Wenliang Dai, Junnan Li, DONGXU LI, Anthony Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale N Fung, and Steven Hoi · 2023
Earlier work this paper cites.
Palm-e: An embodied multimodal language model
Danny Driess, Fei Xia, Mehdi SM Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al · 2023
Cited alongside, same era.
Scaling laws for reward model overoptimization
Leo Gao, John Schulman, and Jacob Hilton · 2023
Cited alongside, same era.
What’s “up” with vision-language models? investigating their struggle with spatial reasoning
Amita Kamath, Jack Hessel, and Kai-Wei Chang · 2023
Cited alongside, same era.
Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
Cited alongside, same era.
Evaluating object hallucination in large vision-language models
Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Xin Zhao, and Ji-Rong Wen · 2023
Cited alongside, same era.
A survey on multimodal large language models for autonomous driving
Can Cui, Yunsheng Ma, Xu Cao, Wenqian Ye, Yang Zhou, Kaizhao Liang, Jintai Chen, Juanwu Lu, Zichong Yang, Kuei-Da Liao, et al · 2024
Closest in time.
Molmo and pixmo: Open weights and open data for state-of-the-art multimodal models
Matt Deitke, Christopher Clark, Sangho Lee, Rohun Tripathi, Yue Yang, Jae Sung Park, Mohammadreza Salehi, Niklas Muennighoff, Kyle Lo, Luca Soldaini, et al · 2024
Closest in time.
Detecting and preventing hallucinations in large vision language models
Anisha Gunjal, Jihan Yin, and Erhan Bas · 2024
Closest in time.
Omnimedvqa: A new large-scale comprehensive evaluation benchmark for medical lvlm
Yutao Hu, Tianbin Li, Quanfeng Lu, Wenqi Shao, Junjun He, Yu Qiao, and Ping Luo · 2024
Closest in time.
Vcoder: Versatile vision encoders for multimodal large language models
Jitesh Jain, Jianwei Yang, and Humphrey Shi · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Pmc-clip: Contrastive language-image pre-training using biomedical documents
Weixiong Lin, Ziheng Zhao, Xiaoman Zhang, Chaoyi Wu, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
Cited alongside, same era.
Visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
Cited alongside, same era.
Med-flamingo: a multimodal medical few-shot learner
Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, and Pranav Rajpurkar · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Cited alongside, same era.
Lvlm-ehub: A comprehensive evaluation benchmark for large vision-language models
Peng Xu, Wenqi Shao, Kaipeng Zhang, Peng Gao, Shuo Liu, Meng Lei, Fanqing Meng, Siyuan Huang, Yu Qiao, and Ping Luo · 2023
Cited alongside, same era.
When and why vision-language models behave like bags-of-words, and what to do about it?
Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, and James Zou · 2023
Cited alongside, same era.
Vip-llava: Making large multimodal models understand arbitrary visual prompts
Mu Cai, Haotian Liu, Siva Karthik Mustikovela, Gregory P Meyer, Yuning Chai, Dennis Park, and Yong Jae Lee · 2024
Cited alongside, same era.
Mitigating object hallucinations in large vision-language models through visual contrastive decoding
Sicong Leng, Hang Zhang, Guanzheng Chen, Xin Li, Shijian Lu, Chunyan Miao, and Lidong Bing · 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
Closest in time.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
Closest in time.
Beyond the hype: A dispassionate look at vision-language models in medical scenario
Yang Nan, Huichi Zhou, Xiaodan Xing, and Guang Yang · 2024
Closest in time.
Multimedeval: A benchmark and a toolkit for evaluating medical vision-language models
Corentin Royer, Bjoern Menze, and Anjany Sekuboyina · 2024
Closest in time.
Cares: A comprehensive benchmark of trustworthiness in medical vision language models
Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, et al · 2024
Closest in time.
Asymptotics of language model alignment
Joy Qiping Yang, Salman Salamatian, Ziteng Sun, Ananda Theertha Suresh, and Ahmad Beirami · 2024
Closest in time.
Micro-bench: A microscopy benchmark for vision-language understanding
Alejandro Lozano, Jeffrey Nirschl, James Burgess, Sanket Rajan Gupte, Yuhui Zhang, Alyssa Unell, and Serena Yeung · 2025
Closest in time.