| Retrieval-augmented generation for knowledge-intensive nlp tasks P Lewis, E Perez, A Piktus, F Petroni, V Karpukhin, N Goyal, H Küttler, ... Advances in neural information processing systems 33, 9459-9474, 2020 | 6159 | 2020 |
| Dense Passage Retrieval for Open-Domain Question Answering. V Karpukhin, B Oguz, S Min, PSH Lewis, L Wu, S Edunov, D Chen, W Yih EMNLP (1), 6769-6781, 2020 | 3567 | 2020 |
| KILT: a benchmark for knowledge intensive language tasks F Petroni, A Piktus, A Fan, P Lewis, M Yazdani, N De Cao, J Thorne, ... arXiv preprint arXiv:2009.02252, 2020 | 534 | 2020 |
| Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 V Karpukhin, B Oguz Dense passage retrieval for opendomain question answering, 2020 | 169 | 2020 |
| Cm3: A causal masked multimodal model of the internet A Aghajanyan, B Huang, C Ross, V Karpukhin, H Xu, N Goyal, D Okhonko, ... arXiv preprint arXiv:2201.07520, 2022 | 159 | 2022 |
| Unik-qa: Unified representations of structured and unstructured knowledge for open-domain question answering B Oguz, X Chen, V Karpukhin, S Peshterliev, D Okhonko, M Schlichtkrull, ... arXiv preprint arXiv:2012.14610, 2020 | 127 | 2020 |
| Training on synthetic noise improves robustness to natural noise in machine translation V Karpukhin, O Levy, J Eisenstein, M Ghazvininejad arXiv preprint arXiv:1902.01509, 2019 | 121 | 2019 |
| Aligned cross entropy for non-autoregressive machine translation M Ghazvininejad, V Karpukhin, L Zettlemoyer, O Levy International Conference on Machine Learning, 3515-3523, 2020 | 116 | 2020 |
| Arcee’s mergekit: A toolkit for merging large language models C Goddard, S Siriwardhana, M Ehghaghi, L Meyers, V Karpukhin, ... Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 84 | 2024 |
| Neurips 2020 efficientqa competition: Systems, analyses and lessons learned S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ... NeurIPS 2020 Competition and Demonstration Track, 86-111, 2021 | 78 | 2021 |
| Multi-task retrieval for knowledge-intensive tasks J Maillard, V Karpukhin, F Petroni, W Yih, B Oğuz, V Stoyanov, G Ghosh arXiv preprint arXiv:2101.00117, 2021 | 64 | 2021 |
| Domain-matched pre-training tasks for dense retrieval B Oğuz, K Lakhotia, A Gupta, P Lewis, V Karpukhin, A Piktus, X Chen, ... arXiv preprint arXiv:2107.13602, 2021 | 60 | 2021 |
| Retrieval-augmented generation for knowledge-intensive NLP tasks. arXiv. org P Lewis, E Perez, A Piktus, F Petroni, V Karpukhin, N Goyal, H Küttler, ... | 60 | 2005 |
| tau Yih P Lewis, E Perez, A Piktus, F Petroni, V Karpukhin, N Goyal, H Küttler, ... W., Rocktäschel, T., Riedel, S., Kiela, D.: Retrieval-augmented generation …, 2021 | 55 | 2021 |
| The web is your oyster-knowledge-intensive NLP against a very large web corpus A Piktus, F Petroni, V Karpukhin, D Okhonko, S Broscheit, G Izacard, ... arXiv preprint arXiv:2112.09924, 2021 | 53 | 2021 |
| Unified open-domain question answering with structured and unstructured knowledge B Oguz, X Chen, V Karpukhin, S Peshterliev, D Okhonko, M Schlichtkrull, ... arXiv preprint arXiv:2012.14610, 2020 | 35 | 2020 |
| Joint verification and reranking for open fact checking over tables M Schlichtkrull, V Karpukhin, B Oğuz, M Lewis, W Yih, S Riedel arXiv preprint arXiv:2012.15115, 2020 | 28 | 2020 |
| Sewon Min, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 V Karpukhin, B Oguz Dense passage retrieval for open-domain question answering. CoRR, abs, 2004 | 21 | 2004 |
| Nonparametric decoding for generative retrieval H Lee, J Kim, H Chang, H Oh, S Yang, V Karpukhin, Y Lu, M Seo arXiv preprint arXiv:2210.02068, 2022 | 19 | 2022 |
| Discourse-aware soft prompting for text generation M Ghazvininejad, V Karpukhin, V Gor, A Celikyilmaz arXiv preprint arXiv:2112.05717, 2021 | 7 | 2021 |
