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 | 2504 | 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 | 762 | 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 | 603* | 2020 |
Metaicl: Learning to learn in context S Min, M Lewis, L Zettlemoyer, H Hajishirzi arXiv preprint arXiv:2110.15943, 2021 | 310 | 2021 |
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 | 264* | 2022 |
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 | 225 | 2019 |
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 | 224* | 2023 |
AmbigQA: Answering Ambiguous Open-domain Questions S Min, J Michael, H Hajishirzi, L Zettlemoyer Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 189 | 2020 |
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 | 176 | 2018 |
Noisy channel language model prompting for few-shot text classification S Min, M Lewis, H Hajishirzi, L Zettlemoyer arXiv preprint arXiv:2108.04106, 2021 | 161 | 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 | 159 | 2019 |
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 | 149 | 2023 |
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 | 142 | 2019 |
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 | 137 | 2017 |
Query-reduction networks for question answering M Seo, S Min, A Farhadi, H Hajishirzi International Conference on Learning Representations (ICLR), 2017 | 132* | 2017 |
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 | 122 | 2020 |
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 | 105 | 2019 |
Neural Speed Reading via Skim-RNN M Seo, S Min, A Farhadi, H Hajishirzi International Conference on Learning Representations (ICLR), 2018 | 104* | 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 | 101* | 2022 |
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ... Proceedings of Machine Learning Research, 2021 | 67 | 2021 |