| GLUE: A multi-task benchmark and analysis platform for natural language understanding A Wang, A Singh, J Michael, F Hill, O Levy, SR Bowman Proceedings of ICLR, 2019 | 3084 | 2019 |
| Superglue: A stickier benchmark for general-purpose language understanding systems A Wang*, Y Pruksachatkun*, N Nangia*, A Singh*, J Michael, F Hill, ... arXiv preprint arXiv:1905.00537, 2019 | 846 | 2019 |
| Neural network acceptability judgments A Warstadt, A Singh, SR Bowman Transactions of the Association for Computational Linguistics 7, 625-641, 2019 | 561 | 2019 |
| Towards VQA Models That Can Read A Singh, V Natarajan, M Shah, Y Jiang, X Chen, D Batra, D Parikh, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 219 | 2019 |
| The hateful memes challenge: Detecting hate speech in multimodal memes D Kiela, H Firooz, A Mohan, V Goswami, A Singh, P Ringshia, ... Advances in Neural Information Processing Systems 33, 2611-2624, 2020 | 143 | 2020 |
| Learning when to communicate at scale in multiagent cooperative and competitive tasks A Singh, T Jain, S Sukhbaatar arXiv preprint arXiv:1812.09755, 2018 | 134* | 2018 |
| MMF: A multimodal framework for vision and language research A Singh, V Goswami, V Natarajan, Y Jiang, X Chen, M Shah, M Rohrbach, ... | 101* | 2020 |
| Iterative answer prediction with pointer-augmented multimodal transformers for textvqa R Hu, A Singh, T Darrell, M Rohrbach Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 90 | 2020 |
| Unit: Multimodal multitask learning with a unified transformer R Hu, A Singh Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 80* | 2021 |
| Dynabench: Rethinking benchmarking in NLP D Kiela, M Bartolo, Y Nie, D Kaushik, A Geiger, Z Wu, B Vidgen, G Prasad, ... arXiv preprint arXiv:2104.14337, 2021 | 78 | 2021 |
| Textcaps: a dataset for image captioning with reading comprehension O Sidorov, R Hu, M Rohrbach, A Singh European conference on computer vision, 742-758, 2020 | 63 | 2020 |
| Learning dynamics model in reinforcement learning by incorporating the long term future NR Ke, A Singh, A Touati, A Goyal, Y Bengio, D Parikh, D Batra arXiv preprint arXiv:1903.01599, 2019 | 55* | 2019 |
| Are we pretraining it right? digging deeper into visio-linguistic pretraining A Singh, V Goswami, D Parikh arXiv preprint arXiv:2004.08744, 2020 | 33* | 2020 |
| Seeing the un-scene: Learning amodal semantic maps for room navigation M Narasimhan, E Wijmans, X Chen, T Darrell, D Batra, D Parikh, A Singh European Conference on Computer Vision, 513-529, 2020 | 27 | 2020 |
| Flava: A foundational language and vision alignment model A Singh, R Hu, V Goswami, G Couairon, W Galuba, M Rohrbach, D Kiela Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 25 | 2022 |
| TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text A Singh, G Pang, M Toh, J Huang, W Galuba, T Hassner Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 17 | 2021 |
| The hateful memes challenge: competition report D Kiela, H Firooz, A Mohan, V Goswami, A Singh, CA Fitzpatrick, P Bull, ... NeurIPS 2020 Competition and Demonstration Track, 344-360, 2021 | 13 | 2021 |
| Human-adversarial visual question answering S Sheng, A Singh, V Goswami, J Magana, T Thrush, W Galuba, D Parikh, ... Advances in Neural Information Processing Systems 34, 20346-20359, 2021 | 11 | 2021 |
| Affirm or reverse? using machine learning to help judges write opinions S Agrawal, E Ash, D Chen, SS Gill, A Singh, K Venkatesan NBER Working Paper 29, 2017 | 9 | 2017 |
| Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality T Thrush, R Jiang, M Bartolo, A Singh, A Williams, D Kiela, C Ross Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 2 | 2022 |
Samuel R. BowmanAssistant Professor, NYUVerified email at nyu.edu
