Fetching the paper…
Reading the bibliography…
Cross-modal encoders for vision-language (VL) tasks are often pretrained with carefully curated vision-language datasets.
1908
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: European conference on computer vision. pp. 740–755. Springer (2014)
2014
Earlier work this paper cites.
Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C.L., Parikh, D.: VQA: Visual Question Answering. In: International Conference on Computer Vision (ICCV) (2015)
2015
Earlier work this paper cites.
Kim, Y., Rush, A.M.: Sequence-level knowledge distillation. arXiv preprint arXiv:1606.07947 (2016)
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
Zhang, P., Goyal, Y., Summers-Stay, D., Batra, D., Parikh, D.: Yin and yang: Balancing and answering binary visual questions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 5014–5022 (2016)
2016
Earlier work this paper cites.
Goyal, Y., Khot, T., Summers-Stay, D., Batra, D., Parikh, D.: Making the v in vqa matter: Elevating the role of image understanding in visual question answering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 6904–6913 (2017)
2017
Earlier work this paper cites.
Sun, C., Shrivastava, A., Singh, S., Gupta, A.: Revisiting unreasonable effectiveness of data in deep learning era. In: Proceedings of the IEEE international conference on computer vision. pp. 843–852 (2017)
2017
Earlier work this paper cites.
Agrawal, A., Batra, D., Parikh, D., Kembhavi, A.: Don’t just assume; look and answer: Overcoming priors for visual question answering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 4971–4980 (2018)
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
Furlanello, T., Lipton, Z., Tschannen, M., Itti, L., Anandkumar, A.: Born again neural networks. In: International Conference on Machine Learning. pp. 1607–1616. PMLR (2018)
2018
Earlier work this paper cites.
Mun, J., Lee, K., Shin, J., Han, B.: Learning to specialize with knowledge distillation for visual question answering. In: NIPS (2018)
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
Sharma, P., Ding, N., Goodman, S., Soricut, R.: Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning. In: Proceedings of ACL (2018)
2018
Earlier work this paper cites.
Campos, R., Mangaravite, V., Pasquali, A., Jorge, A., Nunes, C., Jatowt, A.: Yake! keyword extraction from single documents using multiple local features. Information Sciences 509
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
Noh, H., Kim, T., Mun, J., Han, B.: Transfer learning via unsupervised task discovery for visual question answering. In: Proceedings of the IEEE CVF Conference on Computer Vision and Pattern Recognition. pp. 8385–8394 (2019)
2019
Earlier work this paper cites.
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., et al.: Language models are unsupervised multitask learners. OpenAI blog 1
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
Shah, M., Chen, X., Rohrbach, M., Parikh, D.: Cycle-consistency for robust visual question answering. In: Proceedings of the IEEE CVF Conference on Computer Vision and Pattern Recognition. pp. 6649–6658 (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Chen, L., Wang, D., Gan, Z., Liu, J., Henao, R., Carin, L.: Wasserstein contrastive representation distillation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 16296–16305 (2021)
2021
Later among the works it cites.
Cho, J.W., Kim, D.J., Choi, J., Jung, Y., Kweon, I.S.: Dealing with missing modalities in the visual question answer-difference prediction task through knowledge distillation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1592–1601 (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Fang, Z., Wang, J., Hu, X., Wang, L., Yang, Y., Liu, Z.: Compressing visual-linguistic model via knowledge distillation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 1428–1438 (2021)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zellers, R., Bisk, Y., Farhadi, A., Choi, Y.: From recognition to cognition: Visual commonsense reasoning. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2019)
2019
Cited alongside, same era.
2020
Cited alongside, same era.
Cao, J., Gan, Z., Cheng, Y., Yu, L., Chen, Y.C., Liu, J.: Behind the scene: Revealing the secrets of pre-trained vision-and-language models. In: European Conference on Computer Vision. pp. 565–580. Springer (2020)
2020
Cited alongside, same era.
Chen, Y.C., Li, L., Yu, L., Kholy, A.E., Ahmed, F., Gan, Z., Cheng, Y., Liu, J.: Uniter: Universal image-text representation learning. In: ECCV (2020)
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Li, X., Yin, X., Li, C., Zhang, P., Hu, X., Zhang, L., Wang, L., Hu, H., Dong, L., Wei, F., et al.: Oscar: Object-semantics aligned pre-training for vision-language tasks. In: European Conference on Computer Vision. pp. 121–137. Springer (2020)
2020
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
Huang, Z., Zeng, Z., Huang, Y., Liu, B., Fu, D., Fu, J.: Seeing out of the box: End-to-end pre-training for vision-language representation learning. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Kim, W., Son, B., Kim, I.: Vilt: Vision-and-language transformer without convolution or region supervision. In: ICML (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
Shen, S., Li, L.H., Tan, H., Bansal, M., Rohrbach, A., Chang, K.W., Yao, Z., Keutzer, K.: How much can clip benefit vision-and-language tasks? (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Wang, L., Yoon, K.J.: Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks. IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
Ye, K., Kovashka, A.: A case study of the shortcut effects in visual commonsense reasoning. In: Association for the Advancement of Artificial Intelligence (AAAI) (2021)
2021
Later among the works it cites.
Yu, F., Tang, J., Yin, W., Sun, Y., Tian, H., Wu, H., Wang, H.: Ernie-vil: Knowledge enhanced vision-language representations through scene graph. In: AAAI. vol. 1, p. 12 (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Zhang, P., Li, X., Hu, X., Yang, J., Zhang, L., Wang, L., Choi, Y., Gao, J.: Vinvl: Revisiting visual representations in vision-language models. In: Proceedings of the IEEE CVF Conference on Computer Vision and Pattern Recognition. pp. 5579–5588 (2021)
2021
Later among the works it cites.