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The burgeoning interest in Multimodal Large Language Models (MLLMs), such as OpenAI's GPT-4V(ision), has significantly impacted both academic and industrial realms.
Language models are few-shot learners
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Roberta: A robustly optimized bert pretraining approach
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Conceptnet—a practical commonsense reasoning tool-kit
Hugo Liu and Push Singh. 2004 · 2004
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Abductive commonsense reasoning
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Wen-tau Yih, and Yejin Choi. 2019 · 2019
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Cosmos qa: Machine reading comprehension with contextual commonsense reasoning
Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2019 · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova. 2019 · 2019
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Social iqa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan Le Bras, and Yejin Choi. 2019 · 2019
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Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al. 2020 · 2020
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Aligning ai with shared human values
Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, and Jacob Steinhardt. 2020 · 2020
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Qasc: A dataset for question answering via sentence composition
Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, and Ashish Sabharwal. 2020 · 2020
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Birds have four legs?! numersense: Probing numerical commonsense knowledge of pre-trained language models
Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, and Xiang Ren. 2020 · 2020
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Do neural language models overcome reporting bias?
Vered Shwartz and Yejin Choi. 2020 · 2020
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Pre-training is (almost) all you need: An application to commonsense reasoning
Alexandre Tamborrino, Nicola Pellicanò, Baptiste Pannier, Pascal Voitot, and Louise Naudin. 2020 · 2020
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Do language models learn commonsense knowledge?
Xiang Lorraine Li, Adhiguna Kuncoro, Cyprien de Masson d’Autume, Phil Blunsom, and Aida Nematzadeh. 2021 · 2021
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Riddlesense: Reasoning about riddle questions featuring linguistic creativity and commonsense knowledge
Bill Yuchen Lin, Ziyi Wu, Yichi Yang, Dong-Ho Lee, and Xiang Ren. 2021 · 2021
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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. 2021 · 2021
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Empirical quantitative analysis of covid-19 forecasting models
Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, and Linda Petzold. 2021 · 2021
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Commonsense knowledge reasoning and generation with pre-trained language models: A survey
Prajjwal Bhargava and Vincent Ng. 2022 · 2022
Mm-vid: Advancing video understanding with gpt-4v (ision)
Kevin Lin, Faisal Ahmed, Linjie Li, Chung-Ching Lin, Ehsan Azarnasab, Zhengyuan Yang, Jianfeng Wang, Lin Liang, Zicheng Liu, Yumao Lu, et al. 2023 · 2023
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An evaluation of gpt-4v and gemini in online vqa
Mengchen Liu and Chongyan Chen. 2023 · 2023
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OpenAI. 2023 · 2023
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Artificial general intelligence: Roadmap to achieving human-level capabilities
Abu Rayhan, Rajan Rayhan, and Swajan Rayhan. 2023 · 2023
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An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks
Ke Shen and Mayank Kejriwal. 2023 · 2023
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Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
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 · 2022
Cited alongside, same era.
An in-depth look at gemini’s language abilities
Syeda Nahida Akter, Zichun Yu, Aashiq Muhamed, Tianyue Ou, Alex Bäuerle, Ángel Alexander Cabrera, Krish Dholakia, Chenyan Xiong, and Graham Neubig. 2023 · 2023
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Ning Bian, Xianpei Han, Le Sun, Hongyu Lin, Yaojie Lu, and Ben He. 2023 · 2023
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A challenger to gpt-4v? early explorations of gemini in visual expertise
Chaoyou Fu, Renrui Zhang, Haojia Lin, Zihan Wang, Timin Gao, Yongdong Luo, Yubo Huang, Zhengye Zhang, Longtian Qiu, Gaoxiang Ye, et al. 2023 · 2023
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Large language models as zero-shot conversational recommenders
Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, and Julian McAuley. 2023 · 2023
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Mvp-tuning: Multi-view knowledge retrieval with prompt tuning for commonsense reasoning
Yongfeng Huang, Yanyang Li, Yichong Xu, Lin Zhang, Ruyi Gan, Jiaxing Zhang, and Liwei Wang. 2023 · 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Yuqing Wang, Yun Zhao, and Linda Petzold. 2023 · 2023
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Large language models are better reasoners with self-verification
Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Shengping Liu, Bin Sun, Kang Liu, and Jun Zhao. 2023 · 2023
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The dawn of lmms: Preliminary explorations with gpt-4v (ision)
Zhengyuan Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Chung-Ching Lin, Zicheng Liu, and Lijuan Wang. 2023 · 2023
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L Griffiths, Yuan Cao, and Karthik Narasimhan. 2023 · 2023
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Improving commonsense in vision-language models via knowledge graph riddles
Shuquan Ye, Yujia Xie, Dongdong Chen, Yichong Xu, Lu Yuan, Chenguang Zhu, and Jing Liao. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023 · 2023
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Commonsense knowledge transfer for pre-trained language models
Wangchunshu Zhou, Ronan Le Bras, and Yejin Choi. 2023 · 2023
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