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Multi-modal Large Language Models (MLLMs) are increasingly prominent in the field of artificial intelligence.
What is reasoning? what is an argument?
Douglas N Walton · 1990
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Analogical reasoning: What develops? a review of research and theory
Usha Goswami · 1991
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Deductive reasoning
Philip N Johnson-Laird · 1999
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From here to human-level ai
John McCarthy · 2007
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Abduction
Igor Douven · 2011
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Identifying kinds of reasoning in collective argumentation
AnnaMarie Conner, Laura Singletary, Ryan C. Smith, Patty Anne Wagner, and Richard T. Francisco · 2014
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Cider: Consensus-based image description evaluation, 2015
Ramakrishna Vedantam, C. Lawrence Zitnick, and Devi Parikh · 2015
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Spice: Semantic propositional image caption evaluation, 2016
Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Making the V in VQA matter: Elevating the role of image understanding in Visual Question Answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Human-level intelligence or animal-like abilities?
Adnan Darwiche · 2018
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
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Figureqa: An annotated figure dataset for visual reasoning, 2018
Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, Akos Kadar, Adam Trischler, and Yoshua Bengio · 2018
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Logical reasoning
Bradley H Dowden · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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From recognition to cognition: Visual commonsense reasoning, 2019
Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
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Raven: A dataset for relational and analogical visual reasoning
Chi Zhang, Feng Gao, Baoxiong Jia, Yixin Zhu, and Song-Chun Zhu · 2019
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Ok-vqa: A visual question answering benchmark requiring external knowledge, 2019
Kenneth Marino, Mohammad Rastegari, Ali Farhadi, and Roozbeh Mottaghi · 2019
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From recognition to cognition: Visual commonsense reasoning
Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
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Towards vqa models that can read
Amanpreet Singh, Vivek Natarjan, Meet Shah, Yu Jiang, Xinlei Chen, Devi Parikh, and Marcus Rohrbach · 2019
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Logical reasoning in formal and everyday reasoning tasks
Hugo Bronkhorst, Gerrit Roorda, Cor Suhre, and Martin Goedhart · 2020
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Training verifiers to solve math word problems, 2021
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021
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Perceiver: General perception with iterative attention
Andrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, and Joao Carreira · 2021
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Flamingo: a visual language model for few-shot learning, 2022
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katie Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 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, et al · 2022
Cited alongside, same era.
Winoground: Probing vision and language models for visio-linguistic compositionality, 2022
Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross · 2022
Cited alongside, same era.
Scienceqa: A novel resource for question answering on scholarly articles
Tanik Saikh, Tirthankar Ghosal, Amish Mittal, Asif Ekbal, and Pushpak Bhattacharyya · 2022
Cited alongside, same era.
Towards reasoning in large language models: A survey
Jie Huang and Kevin Chen-Chuan Chang · 2022
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
Instructblip: Towards general-purpose vision-language models with instruction tuning, 2023
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi · 2023
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Otter: A multi-modal model with in-context instruction tuning, 2023
Bo Li, Yuanhan Zhang, Liangyu Chen, Jinghao Wang, Jingkang Yang, and Ziwei Liu · 2023
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Openflamingo: An open-source framework for training large autoregressive vision-language models
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, and Ludwig Schmidt · 2023
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Multimodal chain-of-thought reasoning in language models, 2023
Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, and Alex Smola · 2023
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Mmicl: Empowering vision-language model with multi-modal in-context learning, 2023
Haozhe Zhao, Zefan Cai, Shuzheng Si, Xiaojian Ma, Kaikai An, Liang Chen, Zixuan Liu, Sheng Wang, Wenjuan Han, and Baobao Chang · 2023
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Cited alongside, same era.
Opt: Open pre-trained transformer language models, 2022
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer · 2022
Cited alongside, same era.
Scaling instruction-finetuned language models, 2022
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei · 2022
Cited alongside, same era.
A survey for in-context learning
Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, and Zhifang Sui · 2022
Cited alongside, same era.
Recent advances in natural language processing via large pre-trained language models: A survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, and Dan Roth · 2023
Cited alongside, same era.
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.
Text-to-audio generation using instruction-tuned llm and latent diffusion model
Deepanway Ghosal, Navonil Majumder, Ambuj Mehrish, and Soujanya Poria · 2023
Cited alongside, same era.
Rt-2: Vision-language-action models transfer web knowledge to robotic control
Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, et al · 2023
Cited alongside, same era.
Closest in time.
Improved baselines with visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Yuheng Li, and Yong Jae Lee · 2023
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Seed-bench: Benchmarking multimodal llms with generative comprehension, 2023
Bohao Li, Rui Wang, Guangzhi Wang, Yuying Ge, Yixiao Ge, and Ying Shan · 2023
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Can large language models be an alternative to human evaluations?
Cheng-Han Chiang and Hung-yi Lee · 2023
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Touchstone: Evaluating vision-language models by language models, 2023
Shuai Bai, Shusheng Yang, Jinze Bai, Peng Wang, Xingxuan Zhang, Junyang Lin, Xinggang Wang, Chang Zhou, and Jingren Zhou · 2023
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Visit-bench: A benchmark for vision-language instruction following inspired by real-world use, 2023
Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, and Ludwig Schimdt · 2023
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Mm-vet: Evaluating large multimodal models for integrated capabilities, 2023
Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, and Lijuan Wang · 2023
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Nature language reasoning, a survey
Fei Yu, Hongbo Zhang, and Benyou Wang · 2023
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Emergent analogical reasoning in large language models
Taylor Webb, Keith J Holyoak, and Hongjing Lu · 2023
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Svit: Scaling up visual instruction tuning
Bo Zhao, Boya Wu, and Tiejun Huang · 2023
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Introducing mpt-7b: A new standard for open-source, commercially usable llms
The MosaicML NLP Team · 2023
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Llama: Open and efficient foundation language models, 2023
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
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Introducing our multimodal models, 2023
Rohan Bavishi, Erich Elsen, Curtis Hawthorne, Maxwell Nye, Augustus Odena, Arushi Somani, and Sağnak Taşırlar · 2023
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Releasing Persimmon-8B, 2023
Erich Elsen, Augustus Odena, Maxwell Nye, Sağnak Taşırlar, Tri Dao, Curtis Hawthorne, Deepak Moparthi, and Arushi Somani · 2023
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Internlm-xcomposer: A vision-language large model for advanced text-image comprehension and composition, 2023
Pan Zhang, Xiaoyi Dong, Bin Wang, Yuhang Cao, Chao Xu, Linke Ouyang, Zhiyuan Zhao, Shuangrui Ding, Songyang Zhang, Haodong Duan, Wenwei Zhang, Hang Yan, Xinyue Zhang, Wei Li, Jingwen Li, Kai Chen, Conghui He, Xingcheng Zhang, Yu Qiao, Dahua Lin, and Jiaqi Wang · 2023
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Internlm: A multilingual language model with progressively enhanced capabilities
InternLM Team · 2023
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Llama-adapter v2: Parameter-efficient visual instruction model, 2023
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, Hongsheng Li, and Yu Qiao · 2023
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mplug-owl2: Revolutionizing multi-modal large language model with modality collaboration, 2023
Qinghao Ye, Haiyang Xu, Jiabo Ye, Ming Yan, Anwen Hu, Haowei Liu, Qi Qian, Ji Zhang, Fei Huang, and Jingren Zhou · 2023
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Generative pretraining in multimodality, 2023
Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang, Xiaosong Zhang, Yueze Wang, Hongcheng Gao, Jingjing Liu, Tiejun Huang, and Xinlong Wang · 2023
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Cogvlm: Visual expert for pretrained language models, 2023
Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi, Yan Wang, Junhui Ji, Zhuoyi Yang, Lei Zhao, Xixuan Song, Jiazheng Xu, Bin Xu, Juanzi Li, Yuxiao Dong, Ming Ding, and Jie Tang · 2023
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Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond, 2023
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
Closest in time.
Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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