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Large Language Models (LLMs) have shown remarkable performances on a wide range of natural language understanding and generation tasks.
Tgif-qa: Toward spatio-temporal reasoning in visual question answering
Yunseok Jang, Yale Song, Youngjae Yu, Youngjin Kim, and Gunhee Kim. 2017 · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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Video question answering via gradually refined attention over appearance and motion
Dejing Xu, Zhou Zhao, Jun Xiao, Fei Wu, Hanwang Zhang, Xiangnan He, and Yueting Zhuang. 2017 · 2017
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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 · 2018
Earlier work this paper cites.
Tvqa: Localized, compositional video question answering
Jie Lei, Licheng Yu, Mohit Bansal, and Tamara L Berg. 2018 · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
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Overcoming language priors in visual question answering with adversarial regularization
Sainandan Ramakrishnan, Aishwarya Agrawal, and Stefan Lee. 2018 · 2018
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Rubi: Reducing unimodal biases for visual question answering
Remi Cadene, Corentin Dancette, Matthieu Cord, Devi Parikh, et al. 2019 · 2019
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Activitynet-qa: A dataset for understanding complex web videos via question answering
Zhou Yu, Dejing Xu, Jun Yu, Ting Yu, Zhou Zhao, Yueting Zhuang, and Dacheng Tao. 2019 · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Reasoning with heterogeneous graph alignment for video question answering
Pin Jiang and Yahong Han. 2020 · 2020
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What is more likely to happen next? video-and-language future event prediction
Jie Lei, Licheng Yu, Tamara L Berg, and Mohit Bansal. 2020 · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021 · 2021
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Dramaqa: Character-centered video story understanding with hierarchical qa
Seongho Choi, Kyoung-Woon On, Yu-Jung Heo, Ahjeong Seo, Youwon Jang, Minsu Lee, and Byoung-Tak Zhang. 2021 · 2021
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. 2021 · 2021
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Self-supervised pre-training and contrastive representation learning for multiple-choice video qa
Seonhoon Kim, Seohyeong Jeong, Eunbyul Kim, Inho Kang, and Nojun Kwak. 2021 · 2021
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Hierarchical conditional relation networks for multimodal video question answering
Thao Minh Le, Vuong Le, Svetha Venkatesh, and Truyen Tran. 2021 · 2021
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Counterfactual vqa: A cause-effect look at language bias
Yulei Niu, Kaihua Tang, Hanwang Zhang, Zhiwu Lu, Xian-Sheng Hua, and Ji-Rong Wen. 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, et al. 2021 · 2021
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Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
Cited alongside, same era.
Star: A benchmark for situated reasoning in real-world videos
Bo Wu, Shoubin Yu, Zhenfang Chen, Joshua B Tenenbaum, and Chuang Gan. 2021 · 2021
Cited alongside, same era.
Next-qa: Next phase of question-answering to explaining temporal actions
Junbin Xiao, Xindi Shang, Angela Yao, and Tat-Seng Chua. 2021 · 2021
Cited alongside, same era.
Just ask: Learning to answer questions from millions of narrated videos
Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, and Cordelia Schmid. 2021 · 2021
Cited alongside, same era.
Learning from inside: Self-driven siamese sampling and reasoning for video question answering
Video graph transformer for video question answering
Junbin Xiao, Pan Zhou, Tat-Seng Chua, and Shuicheng Yan. 2022 · 2022
Later among the works it cites.
Zero-shot video question answering via frozen bidirectional language models
Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, and Cordelia Schmid. 2022 · 2022
Later among the works it cites.
Hitea: Hierarchical temporal-aware video-language pre-training
Qinghao Ye, Guohai Xu, Ming Yan, Haiyang Xu, Qi Qian, Ji Zhang, and Fei Huang. 2022 · 2022
Later among the works it cites.
Say what you mean! large language models speak too positively about negative commonsense knowledge
Jiangjie Chen, Wei Shi, Ziquan Fu, Sijie Cheng, Lei Li, and Yanghua Xiao. 2023 · 2023
Closest in time.
Vindlu: A recipe for effective video-and-language pretraining
Feng Cheng, Xizi Wang, Jie Lei, David Crandall, Mohit Bansal, and Gedas Bertasius. 2023 · 2023
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Weijiang Yu, Haoteng Zheng, Mengfei Li, Lei Ji, Lijun Wu, Nong Xiao, and Nan Duan. 2021 · 2021
Cited alongside, same era.
Merlot: Multimodal neural script knowledge models
Rowan Zellers, Ximing Lu, Jack Hessel, Youngjae Yu, Jae Sung Park, Jize Cao, Ali Farhadi, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
Situatedqa: Incorporating extra-linguistic contexts into qa
Michael JQ Zhang and Eunsol Choi. 2021 · 2021
Cited alongside, same era.
Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2021
Cited alongside, same era.
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 · 2022
Cited alongside, same era.
Revisiting the" video" in video-language understanding
Shyamal Buch, Cristóbal Eyzaguirre, Adrien Gaidon, Jiajun Wu, Li Fei-Fei, and Juan Carlos Niebles. 2022 · 2022
Cited alongside, same era.
Context-aware abbreviation expansion using large language models
Shanqing Cai, Subhashini Venugopalan, Katrin Tomanek, Ajit Narayanan, Meredith R Morris, and Michael P Brenner. 2022 · 2022
Cited alongside, same era.
Increasing diversity while maintaining accuracy: Text data generation with large language models and human interventions
John Joon Young Chung, Ece Kamar, and Saleema Amershi. 2023 · 2023
Closest in time.
Mitigating label biases for in-context learning
Yu Fei, Yifan Hou, Zeming Chen, and Antoine Bosselut. 2023 · 2023
Closest in time.
Mist: Multi-modal iterative spatial-temporal transformer for long-form video question answering
Difei Gao, Luowei Zhou, Lei Ji, Linchao Zhu, Yi Yang, and Mike Zheng Shou. 2023 · 2023
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Llm-blender: Ensembling large language models with pairwise ranking and generative fusion
Dongfu Jiang, Xiang Ren, and Bill Yuchen Lin. 2023 · 2023
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Knowledge-constrained answer generation for open-ended video question answering
Yao Jin, Guocheng Niu, Xinyan Xiao, Jian Zhang, Xi Peng, and Jun Yu. 2023 · 2023
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Evaluating open-domain question answering in the era of large language models
Ehsan Kamalloo, Nouha Dziri, Charles LA Clarke, and Davood Rafiei. 2023 · 2023
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Causal reasoning and large language models: Opening a new frontier for causality
Emre Kıcıman, Robert Ness, Amit Sharma, and Chenhao Tan. 2023 · 2023
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Open-vocabulary video question answering: A new benchmark for evaluating the generalizability of video question answering models
Dohwan Ko, Ji Soo Lee, Miso Choi, Jaewon Chu, Jihwan Park, and Hyunwoo J Kim. 2023 · 2023
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Revealing single frame bias for video-and-language learning
Jie Lei, Tamara L Berg, and Mohit Bansal. 2023 · 2023
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Evaluating the logical reasoning ability of chatgpt and gpt-4
Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, Jian Liu, Qiji Zhou, and Yue Zhang. 2023 · 2023
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Can large language models build causal graphs?
Stephanie Long, Tibor Schuster, Alexandre Piché, ServiceNow Research, et al. 2023 · 2023
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Thinksum: Probabilistic reasoning over sets using large language models
Batu Ozturkler, Nikolay Malkin, Zhen Wang, and Nebojsa Jojic. 2023 · 2023
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Towards benchmarking and improving the temporal reasoning capability of large language models
Qingyu Tan, Hwee Tou Ng, and Lidong Bing. 2023 · 2023
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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 · 2023
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Self-chained image-language model for video localization and question answering
Shoubin Yu, Jaemin Cho, Prateek Yadav, and Mohit Bansal. 2023 · 2023
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