| Vqa: Visual question answering S Antol, A Agrawal, J Lu, M Mitchell, D Batra, CL Zitnick, D Parikh Proceedings of the IEEE international conference on computer vision, 2425-2433, 2015 | 5892 | 2015 |
| Don't just assume; look and answer: Overcoming priors for visual question answering A Agrawal, D Batra, D Parikh, A Kembhavi Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 663 | 2018 |
| Visual storytelling TH Huang, F Ferraro, N Mostafazadeh, I Misra, A Agrawal, J Devlin, ... Proceedings of the 2016 conference of the North American chapter of the …, 2016 | 446 | 2016 |
| Analyzing the behavior of visual question answering models A Agrawal, D Batra, D Parikh arXiv preprint arXiv:1606.07356, 2016 | 359 | 2016 |
| Overcoming language priors in visual question answering with adversarial regularization S Ramakrishnan, A Agrawal, S Lee Advances in Neural Information Processing Systems 31, 2018 | 232 | 2018 |
| C-vqa: A compositional split of the visual question answering (vqa) v1. 0 dataset A Agrawal, A Kembhavi, D Batra, D Parikh arXiv preprint arXiv:1704.08243, 2017 | 80 | 2017 |
| Measuring machine intelligence through visual question answering CL Zitnick, A Agrawal, S Antol, M Mitchell, D Batra, D Parikh AI Magazine 37 (1), 63-72, 2016 | 39 | 2016 |
| Resolving language and vision ambiguities together: Joint segmentation & prepositional attachment resolution in captioned scenes G Christie, A Laddha, A Agrawal, S Antol, Y Goyal, K Kochersberger, ... arXiv preprint arXiv:1604.02125, 2016 | 34 | 2016 |
| Mapl: Parameter-efficient adaptation of unimodal pre-trained models for vision-language few-shot prompting O Mañas, P Rodriguez, S Ahmadi, A Nematzadeh, Y Goyal, A Agrawal arXiv preprint arXiv:2210.07179, 2022 | 27 | 2022 |
| Reassessing evaluation practices in visual question answering: A case study on out-of-distribution generalization A Agrawal, I Kajić, E Bugliarello, E Davoodi, A Gergely, P Blunsom, ... arXiv preprint arXiv:2205.12191, 2022 | 17 | 2022 |
| Measuring progress in fine-grained vision-and-language understanding E Bugliarello, L Sartran, A Agrawal, LA Hendricks, A Nematzadeh arXiv preprint arXiv:2305.07558, 2023 | 16 | 2023 |
| Resolving vision and language ambiguities together: Joint segmentation & prepositional attachment resolution in captioned scenes G Christie, A Laddha, A Agrawal, S Antol, Y Goyal, K Kochersberger, ... Computer Vision and Image Understanding 163, 101-112, 2017 | 13 | 2017 |
| Visual storytelling F Ferraro, N Mostafazadeh, I Misra, A Agrawal, J Devlin, R Girshick, X He, ... arXiv preprint arXiv:1604.03968, 2016 | 11 | 2016 |
| Improving automatic vqa evaluation using large language models O Mañas, B Krojer, A Agrawal Proceedings of the AAAI Conference on Artificial Intelligence 38 (5), 4171-4179, 2024 | 6 | 2024 |
| Visual question answering S Antol, A Agrawal, J Lu, M Mitchell, D Batra, CL Zitnick, DP Vqa Proceedings of the IEEE International Conference on Computer Vision, 2022 | 4 | 2022 |
| Improving text-to-image consistency via automatic prompt optimization O Mañas, P Astolfi, M Hall, C Ross, J Urbanek, A Williams, A Agrawal, ... arXiv preprint arXiv:2403.17804, 2024 | 3 | 2024 |
| An examination of the robustness of reference-free image captioning evaluation metrics S Ahmadi, A Agrawal arXiv preprint arXiv:2305.14998, 2023 | 3 | 2023 |
| Vision-language pretraining: Current trends and the future A Agrawal, D Teney, A Nematzadeh Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 3 | 2022 |
| VQA: Visual Question Answering www. visualqa. org A Agrawal, J Lu, S Antol, M Mitchell, CL Zitnick, D Batra, D Parikh Proceedings of the IEEE international conference on computer vision, 2425-2433, 2015 | 3 | 2015 |
| Generating diverse programs with instruction conditioned reinforced adversarial learning A Agrawal, M Malinowski, F Hill, A Eslami, O Vinyals, T Kulkarni arXiv preprint arXiv:1812.00898, 2018 | 2 | 2018 |
