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Self-supervised bidirectional transformer models such as BERT have led to dramatic improvements in a wide variety of textual classification tasks.
MFAS: multimodal fusion architecture search
Juan-Manuel Pérez-Rúa, Valentin Vielzeuf, Stéphane Pateux, Moez Baccouche, and Frédéric Jurie. 2019 · 1903
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Videobert: A joint model for video and language representation learning
Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, and Cordelia Schmid. 2019 · 1904
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What makes training multi-modal networks hard?
Weiyao Wang, Du Tran, and Matt Feiszli. 2019 · 1905
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Multimodal transformer for unaligned multimodal language sequences
Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J. Zico Kolter, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2019 · 1906
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Visualbert: A simple and performant baseline for vision and language
Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, and Kai-Wei Chang. 2019 · 1908
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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 · 1908
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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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Lxmert: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal. 2019 · 1908
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A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston. 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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Wsabie: Scaling up to large vocabulary image annotation
Jason Weston, Samy Bengio, and Nicolas Usunier. 2011 · 2011
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Devise: A deep visual-semantic embedding model
Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, Tomas Mikolov, et al. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Zero-shot learning through cross-modal transfer
Richard Socher, Milind Ganjoo, Christopher D Manning, and Andrew Ng. 2013 · 2013
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Multimodal distributional semantics
Elia Bruni, Nam-Khanh Tran, and Marco Baroni. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
Maxime Oquab, Leon Bottou, Ivan Laptev, and Josef Sivic. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Cnn features off-the-shelf: an astounding baseline for recognition
Ali Sharif Razavian, Hossein Azizpour, Josephine Sullivan, and Stefan Carlsson. 2014 · 2014
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From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier. 2014 · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning. 2015 · 2015
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Deep Embodiment: Grounding Semantics in Perceptual Modalities
Douwe Kiela. 2017 · 2017
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PyTorch: Tensors and dynamic neural networks in python with strong GPU acceleration
Adam Paszke, Sam Gross, Soumith Chintala, and Gregory Chanan. 2017 · 2017
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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 · 2017
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Tensor fusion network for multimodal sentiment analysis
Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency. 2017 · 2017
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Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R Bowman, and Noah A Smith. 2018 · 2018
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Semi-supervised sequence learning
Andrew M Dai and Quoc V Le. 2015 · 2015
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 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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Recipe recognition with large multimodal food dataset
Xin Wang, Devinder Kumar, Nicolas Thome, Matthieu Cord, and Frederic Precioso. 2015 · 2015
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Grounding distributional semantics in the visual world
Marco Baroni. 2016 · 2016
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Automatic description generation from images: A survey of models, datasets, and evaluation measures
Raffaella Bernardi, Ruket Cakici, Desmond Elliott, Aykut Erdem, Erkut Erdem, Nazli Ikizler-Cinbis, Frank Keller, Adrian Muscat, and Barbara Plank. 2016 · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
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Efficient large-scale multi-modal classification
Douwe Kiela, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2018 · 2018
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, and Aaron Courville. 2018 · 2018
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Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks
Jason Phang, Thibault Févry, and Samuel R. Bowman. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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Centralnet: a multilayer approach for multimodal fusion
Valentin Vielzeuf, Alexis Lechervy, Stephane Pateux, and Frederic Jurie. 2018 · 2018
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Grounded textual entailment
Hoa Trong Vu, Claudio Greco, Aliia Erofeeva, Somayeh Jafaritazehjan, Guido Linders, Marc Tanti, Alberto Testoni, Raffaella Bernardi, and Albert Gatt. 2018 · 2018
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Multimodal machine learning: A survey and taxonomy
Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency. 2019 · 2019
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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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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Aishwarya Agrawal, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2019 · 2019
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