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Adapting general multimodal large language models (MLLMs) to specific domains, such as scientific and industrial fields, is highly significant in promoting their practical applications.
Ensemble methods in machine learning
Thomas G Dietterich. 2000 · 2000
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Pathvqa: 30000+ questions for medical visual question answering
Xuehai He, Yichen Zhang, Luntian Mou, Eric Xing, and Pengtao Xie. 2020 · 2003
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Language models are few-shot learners
Tom B Brown. 2020 · 2005
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Bag-of-visual-words and spatial extensions for land-use classification
Yi Yang and Shawn Newsam. 2010 · 2010
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Food-101–mining discriminative components with random forests
Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool. 2014 · 2014
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Deep semantic understanding of high resolution remote sensing image
Bo Qu, Xuelong Li, Dacheng Tao, and Xiaoqiang Lu. 2016 · 2016
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Learning cross-modal embeddings for cooking recipes and food images
Amaia Salvador, Nicholas Hynes, Yusuf Aytar, Javier Marin, Ferda Ofli, Ingmar Weber, and Antonio Torralba. 2017 · 2017
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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
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, and 1 others. 2018 · 2018
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CLRS: continual learning benchmark for remote sensing image scene classification
Haifeng Li, Hao Jiang, Xin Gu, Jian Peng, Wenbo Li, Liang Hong, and Chao Tao. 2020 · 2020
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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
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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, and 1 others. 2021 · 2021
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Floodnet: A high resolution aerial imagery dataset for post flood scene understanding
Maryam Rahnemoonfar, Tashnim Chowdhury, Argho Sarkar, Debvrat Varshney, Masoud Yari, and Robin Roberson Murphy. 2021 · 2021
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Nutrition5k: Towards automatic nutritional understanding of generic food
Quin Thames, Arjun Karpur, Wade Norris, Fangting Xia, Liviu Panait, Tobias Weyand, and Jack Sim. 2021 · 2021
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2021 · 2021
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A large-scale benchmark for food image segmentation
Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven CH Hoi, and Qianru Sun. 2021 · 2021
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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, and 1 others. 2022 · 2022
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Nwpu-captions dataset and mlca-net for remote sensing image captioning
Qimin Cheng, Haiyan Huang, Yuan Xu, Yuzhuo Zhou, Huanying Li, and Zhongyuan Wang. 2022 · 2022
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Learning instructions with unlabeled data for zero-shot cross-task generalization
Yuxian Gu, Pei Ke, Xiaoyan Zhu, and Minlie Huang. 2022 · 2022
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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 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, and 1 others. 2022 · 2022
Genixer: Empowering multimodal large language models as a powerful data generator
Henry Hengyuan Zhao, Pan Zhou, and Mike Zheng Shou. 2023 · 2023
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Fintral: A family of gpt-4 level multimodal financial large language models
Gagan Bhatia, El Moatez Billah Nagoudi, Hasan Cavusoglu, and Muhammad Abdul-Mageed. 2024 · 2024
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Open-llava-next: An open-source implementation of llava-next series for facilitating the large multi-modal model community
Lin Chen and Long Xing. 2024 · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, and 1 others. 2024 · 2024
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Exploring a fine-grained multiscale method for cross-modal remote sensing image retrieval
Zhiqiang Yuan, Wenkai Zhang, Kun Fu, Xuan Li, Chubo Deng, Hongqi Wang, and Xian Sun. 2022 · 2022
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Sharegpt4v: Improving large multi-modal models with better captions
Lin Chen, Jinsong Li, Xiaoyi Dong, Pan Zhang, Conghui He, Jiaqi Wang, Feng Zhao, and Dahua Lin. 2023 · 2023
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, and 1 others. 2023 · 2023
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Language is not all you need: Aligning perception with language models
Shaohan Huang, Li Dong, Wenhui Wang, Yaru Hao, Saksham Singhal, Shuming Ma, Tengchao Lv, Lei Cui, Owais Khan Mohammed, Barun Patra, and 1 others. 2023 · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
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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 · 2023
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Orca: Progressive learning from complex explanation traces of gpt-4
Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, and Ahmed Awadallah. 2023 · 2023
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Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, and 1 others. 2024 · 2024
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Llm2llm: Boosting llms with novel iterative data enhancement
Nicholas Lee, Thanakul Wattanawong, Sehoon Kim, Karttikeya Mangalam, Sheng Shen, Gopala Anumanchipali, Michael W Mahoney, Kurt Keutzer, and Amir Gholami. 2024 · 2024
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Dolphins: Multimodal language model for driving
Yingzi Ma, Yulong Cao, Jiachen Sun, Marco Pavone, and Chaowei Xiao. 2024 · 2024
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Llava-chef: A multi-modal generative model for food recipes
Fnu Mohbat and Mohammed J Zaki. 2024 · 2024
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Grounding multimodal large language models to the world
Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, Qixiang Ye, and Furu Wei. 2024 · 2024
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Chameleon: Mixed-modal early-fusion foundation models
Chameleon Team. 2024 · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, and 1 others. 2024 · 2024
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Instructseg: Unifying instructed visual segmentation with multi-modal large language models
Cong Wei, Yujie Zhong, Haoxian Tan, Yingsen Zeng, Yong Liu, Zheng Zhao, and Yujiu Yang. 2024 · 2024
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Vision-flan: Scaling human-labeled tasks in visual instruction tuning
Zhiyang Xu, Chao Feng, Rulin Shao, Trevor Ashby, Ying Shen, Di Jin, Yu Cheng, Qifan Wang, and Lifu Huang. 2024 · 2024
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Mammoth2: Scaling instructions from the web
Xiang Yue, Tuney Zheng, Ge Zhang, and Wenhu Chen. 2024 · 2024
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Earthgpt: A universal multi-modal large language model for multi-sensor image comprehension in remote sensing domain
Wei Zhang, Miaoxin Cai, Tong Zhang, Yin Zhuang, and Xuerui Mao. 2024 · 2024
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Llamafactory: Unified efficient fine-tuning of 100+ language models
Yaowei Zheng, Richong Zhang, Junhao Zhang, Yanhan Ye, Zheyan Luo, Zhangchi Feng, and Yongqiang Ma. 2024 · 2024
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