| Dense Passage Retrieval for Open-Domain Question Answering V Karpukhin, B Oğuz, S Min, L Wu, S Edunov, D Chen, W Yih Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 3799 | 2020 |
| Rethinking the role of demonstrations: What makes in-context learning work? S Min, X Lyu, A Holtzman, M Artetxe, M Lewis, H Hajishirzi, L Zettlemoyer arXiv preprint arXiv:2202.12837, 2022 | 1329 | 2022 |
| Unifiedqa: Crossing format boundaries with a single qa system D Khashabi, S Min, T Khot, A Sabharwal, O Tafjord, P Clark, H Hajishirzi Findings of Empirical Methods in Natural Language Processing (EMNLP), 2020 | 749* | 2020 |
| Replug: Retrieval-augmented black-box language models W Shi, S Min, M Yasunaga, M Seo, R James, M Lewis, L Zettlemoyer, ... arXiv preprint arXiv:2301.12652, 2023 | 536* | 2023 |
| Factscore: Fine-grained atomic evaluation of factual precision in long form text generation S Min, K Krishna, X Lyu, M Lewis, W Yih, PW Koh, M Iyyer, L Zettlemoyer, ... arXiv preprint arXiv:2305.14251, 2023 | 517 | 2023 |
| Measuring and narrowing the compositionality gap in language models O Press, M Zhang, S Min, L Schmidt, NA Smith, M Lewis arXiv preprint arXiv:2210.03350, 2022 | 483* | 2022 |
| Metaicl: Learning to learn in context S Min, M Lewis, L Zettlemoyer, H Hajishirzi arXiv preprint arXiv:2110.15943, 2021 | 463 | 2021 |
| AmbigQA: Answering Ambiguous Open-domain Questions S Min, J Michael, H Hajishirzi, L Zettlemoyer Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 279 | 2020 |
| Multi-hop Reading Comprehension through Question Decomposition and Rescoring S Min, V Zhong, L Zettlemoyer, H Hajishirzi Annual Meeting of the Association for Computational Linguistics (ACL), 2019 | 267 | 2019 |
| Efficient and Robust Question Answering from Minimal Context over Documents S Min, V Zhong, R Socher, C Xiong Annual Meeting of the Association for Computational Linguistics (ACL), 2018 | 265* | 2018 |
| Towards understanding chain-of-thought prompting: An empirical study of what matters B Wang, S Min, X Deng, J Shen, Y Wu, L Zettlemoyer, H Sun arXiv preprint arXiv:2212.10001, 2022 | 221* | 2022 |
| Noisy channel language model prompting for few-shot text classification S Min, M Lewis, H Hajishirzi, L Zettlemoyer arXiv preprint arXiv:2108.04106, 2021 | 219 | 2021 |
| A Discrete Hard EM Approach for Weakly Supervised Question Answering S Min, D Chen, H Hajishirzi, L Zettlemoyer Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019 | 178 | 2019 |
| Compositional Questions Do Not Necessitate Multi-hop Reasoning S Min, E Wallace, S Singh, M Gardner, H Hajishirzi, L Zettlemoyer Annual Meeting of the Association for Computational Linguistics (ACL), 2019 | 153 | 2019 |
| Efficient One-Pass End-to-End Entity Linking for Questions BZ Li, S Min, S Iyer, Y Mehdad, W Yih Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 151 | 2020 |
| Retrieval-based language models and applications A Asai, S Min, Z Zhong, D Chen Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 140* | 2023 |
| Question Answering through Transfer Learning from Large Fine-grained Supervision Data S Min, M Seo, H Hajishirzi Annual Meeting of the Association for Computational Linguistics (ACL), 2017 | 138 | 2017 |
| Query-reduction networks for question answering M Seo, S Min, A Farhadi, H Hajishirzi International Conference on Learning Representations (ICLR), 2017 | 137* | 2017 |
| Knowledge guided text retrieval and reading for open domain question answering S Min, D Chen, L Zettlemoyer, H Hajishirzi arXiv preprint arXiv:1911.03868, 2019 | 119 | 2019 |
| Do membership inference attacks work on large language models? M Duan, A Suri, N Mireshghallah, S Min, W Shi, L Zettlemoyer, Y Tsvetkov, ... arXiv preprint arXiv:2402.07841, 2024 | 112* | 2024 |
Hannaneh HajishirziUniversity of Washington; Allen AIEmail verificata su cs.washington.edu