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Visual grounding is a promising path toward more robust and accurate Natural Language Processing (NLP) models.
SuperGLUE: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 1905
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Vl-bert: Pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai. 2019 · 1908
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Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 1909
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Metaphors we Live by
George Lakoff and Mark Johnson. 1980 · 1980
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2002
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Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, et al. 2020 · 2004
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
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The penn discourse treebank 2.0
Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Miltsakaki, Livio Robaldo, Aravind Joshi, and Bonnie Webber. 2008 · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
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Im2text: Describing images using 1 million captioned photographs
Vicente Ordonez, Girish Kulkarni, and Tamara L. Berg. 2011 · 2011
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Multimodal distributional semantics
Elia Bruni, Nam-Khanh Tran, and Marco Baroni. 2014 · 2014
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Learning image embeddings using convolutional neural networks for improved multi-modal semantics
Douwe Kiela and Léon Bottou. 2014 · 2014
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Improving multi-modal representations using image dispersion: Why less is sometimes more
Douwe Kiela, Felix Hill, Anna Korhonen, and Stephen Clark. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
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Learning grounded meaning representations with autoencoders
Carina Silberer and Mirella Lapata. 2014 · 2014
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Fast r-cnn
Ross Girshick. 2015 · 2015
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Combining language and vision with a multimodal skip-gram model
Angeliki Lazaridou, Nghia The Pham, and Marco Baroni. 2015 · 2015
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Advances in pre-training distributed word representations
Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin. 2018 · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee. 2019 · 2019
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Probing neural network comprehension of natural language arguments
Timothy Niven and Hung-Yu Kao. 2019 · 2019
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Cited alongside, same era.
A shared task on multimodal machine translation and crosslingual image description
Lucia Specia, Stella Frank, Khalil Sima’an, and Desmond Elliott. 2016 · 2016
Cited alongside, same era.
Imagined visual representations as multimodal embeddings
Guillem Collell, Ted Zhang, and Marie-Francine Moens. 2017 · 2017
Cited alongside, same era.
Findings of the second shared task on multimodal machine translation and multilingual image description
Desmond Elliott, Stella Frank, Loïc Barrault, Fethi Bougares, and Lucia Specia. 2017 · 2017
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Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2017 · 2017
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Vu amsterdam metaphor corpus
Tina Krennmayr and Gerard Steen. 2017 · 2017
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Ordinal common-sense inference
Sheng Zhang, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2017 · 2017
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Nils Reimers and Iryna Gurevych. 2019 · 2019
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LXMERT: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal. 2019 · 2019
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BERT has a mouth, and it must speak: BERT as a Markov random field language model
Alex Wang and Kyunghyun Cho. 2019 · 2019
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Uniter: Universal image-text representation learning
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu. 2020 · 2020
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Proceedings of the Second Workshop on Figurative Language Processing . ACL
Beata Beigman Klebanov, Ekaterina Shutova, Patricia Lichtenstein, Smaranda Muresan, Chee Wee, Anna Feldman, and Debanjan Ghosh, editors. 2020 · 2020
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K-BERT: Enabling language representation with knowledge graph
Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, and Ping Wang. 2020 · 2020
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Self-training with noisy student improves imagenet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy, and Quoc V. Le. 2020 · 2020
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Neural machine translation with universal visual representation
Zhuosheng Zhang, Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita, Zuchao Li, and Hai Zhao. 2020 · 2020
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Vokenization: Improving language understanding with contextualized, visual-grounded supervision
Hao Tan and Mohit Bansal. 2020 · 2080
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