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We propose the Vision-and-Augmented-Language Transformer (VAuLT).
Microsoft coco: Common objects in context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
Earlier work this paper cites.
Heart versus head: Do judges follow the law of follow their feelings
Wistrich, A. J., Rachlinski, J. J., and Guthrie, C · 2014
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Vqa: Visual question answering
Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Lawrence Zitnick, C., and Parikh, D · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Ren, S., He, K., Girshick, R., and Sun, J · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J · 2016
Earlier work this paper cites.
Sentiment analysis on multi-view social data
Niu, T., Zhu, S., Pang, L., and El-Saddik, A · 2016
Earlier work this paper cites.
Ntua-slp at semeval-2018 task 1: Predicting affective content in tweets with deep attentive rnns and transfer learning
Baziotis, C., Nikolaos, A., Chronopoulou, A., Kolovou, A., Paraskevopoulos, G., Ellinas, N., Narayanan, S., and Potamianos, A · 2018
Earlier work this paper cites.
The global organization of social media disinformation campaigns
Bradshaw, S., and Howard, P. N · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K · 2018
Earlier work this paper cites.
Dictionaries and distributions: Combining expert knowledge and large scale textual data content analysis
Garten, J., Hoover, J., Johnson, K. M., Boghrati, R., Iskiwitch, C., and Dehghani, M · 2018
Earlier work this paper cites.
Moral framing and charitable donation: Integrating exploratory social media analyses and confirmatory experimentation
Hoover, J., Johnson, K., Boghrati, R., Graham, J., and Dehghani, M · 2018
Cited alongside, same era.
Multimodal sentiment analysis to explore the structure of emotions
Hu, A., and Flaxman, S · 2018
Cited alongside, same era.
Semeval-2018 task 1: Affect in tweets
Mohammad, S., Bravo-Marquez, F., Salameh, M., and Kiritchenko, S · 2018
Cited alongside, same era.
Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Lu, J., Batra, D., Parikh, D., and Lee, S · 2019
Cited alongside, same era.
Vl-bert: Pre-training of generic visual-linguistic representations
Su, W., Zhu, X., Cao, Y., Li, B., Lu, L., Wei, F., and Dai, J · 2019
Cited alongside, same era.
Semeval-2020 task 8: Memotion analysis–the visuo-lingual metaphor!
Sharma, C., Bhageria, D., Scott, W., Pykl, S., Das, A., Chakraborty, T., Pulabaigari, V., and Gamback, B · 2020
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The rise of affectivism
Dukes, D., Abrams, K., Adolphs, R., Ahmed, M. E., Beatty, A., Berridge, K. C., Broomhall, S., Brosch, T., Campos, J. J., Clay, Z., et al · 2021
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Investigating the role of group-based morality in extreme behavioral expressions of prejudice
Hoover, J., Atari, M., Mostafazadeh Davani, A., Kennedy, B., Portillo-Wightman, G., Yeh, L., and Dehghani, M · 2021
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Exploiting bert for multimodal target sentiment classification through input space translation
Khan, Z., and Fu, Y · 2021
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Vilt: Vision-and-language transformer without convolution or region supervision
Kim, W., Son, B., and Kim, I · 2021
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Wahl-Jorgensen, K · 2019
Cited alongside, same era.
Adapting bert for target-oriented multimodal sentiment classification
Yu, J., and Jiang, J · 2019
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al · 2020
Cited alongside, same era.
What happens to bert embeddings during fine-tuning?
Merchant, A., Rahimtoroghi, E., Pavlick, E., and Tenney, I · 2020
Cited alongside, same era.
Bertweet: A pre-trained language model for english tweets
Nguyen, D. Q., Vu, T., and Nguyen, A. T · 2020
Cited alongside, same era.
Ethical pitfalls for natural language processing in psychology
Alfano, M., Sullivan, E., and Fard, A. E · 2022
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Leveraging label correlations in a multi-label setting: A case study in emotion
Chochlakis, G., Mahajan, G., Baruah, S., Burghardt, K., Lerman, K., and Narayanan, S · 2022
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Climb: A continual learning benchmark for vision-and-language tasks
Srinivasan, T., Chang, T.-Y., Alva, L. L. P., Chochlakis, G., Rostami, M., and Thomason, J · 2022
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Multimodal sentiment analysis with image-text interaction network
Zhu, T., Li, L., Yang, J., Zhao, S., Liu, H., and Qian, J · 2022
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