| Videoclip: Contrastive pre-training for zero-shot video-text understanding H Xu, G Ghosh, PY Huang, D Okhonko, A Aghajanyan, F Metze, ... arXiv preprint arXiv:2109.14084, 2021 | 586 | 2021 |
| Fairseq S2T: Fast speech-to-text modeling with fairseq C Wang, Y Tang, X Ma, A Wu, S Popuri, D Okhonko, J Pino arXiv preprint arXiv:2010.05171, 2020 | 275 | 2020 |
| Transformers with convolutional context for ASR A Mohamed, D Okhonko, L Zettlemoyer arXiv preprint arXiv:1904.11660, 2019 | 191 | 2019 |
| 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 | 123 | 2020 |
| Htlm: Hyper-text pre-training and prompting of language models A Aghajanyan, D Okhonko, M Lewis, M Joshi, H Xu, G Ghosh, ... arXiv preprint arXiv:2107.06955, 2021 | 82 | 2021 |
| 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 | 79 | 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 | 52 | 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 |
| Legonn: Building modular encoder-decoder models S Dalmia, D Okhonko, M Lewis, S Edunov, S Watanabe, F Metze, ... IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2023 | 18 | 2023 |
| CCQA: A new web-scale question answering dataset for model pre-training P Huber, A Aghajanyan, B Oğuz, D Okhonko, W Yih, S Gupta, X Chen arXiv preprint arXiv:2110.07731, 2021 | 11 | 2021 |
| Transformers with convolutional context for ASR. arXiv 2019 A Mohamed, D Okhonko, L Zettlemoyer arXiv preprint arXiv:1904.11660, 0 | 7 | |
| Training asr models by generation of contextual information K Singh, D Okhonko, J Liu, Y Wang, F Zhang, R Girshick, S Edunov, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 6 | 2020 |
| Determining information describing objects maintained by an online system by applying rules to input received via a form provided by the online system D Okhonko, P Agarwal, AF De Oliveira US Patent 10,460,025, 2019 | | 2019 |
| The Web Is Your Oyster-Knowledge-Intensive NLP against a Very Large Web Corpus APFPV Karpukhin, D Okhonko, S Broscheit, G Izacard, P Lewis, B Oguz | | |
Luke ZettlemoyerUniversity of Washington; MetaE-mail megerősítve itt: cs.washington.edu