| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 3090 | 2021 |
| COMET: Commonsense transformers for automatic knowledge graph construction A Bosselut, H Rashkin, M Sap, C Malaviya, A Celikyilmaz, Y Choi ACL 2019, 2019 | 982 | 2019 |
| QA-GNN: Reasoning with language models and knowledge graphs for question answering M Yasunaga, H Ren, A Bosselut, P Liang, J Leskovec NAACL 2021, 2021 | 480 | 2021 |
| Deep communicating agents for abstractive summarization A Celikyilmaz, A Bosselut, X He, Y Choi NAACL 2018, 2018 | 403 | 2018 |
| (comet-) atomic 2020: On symbolic and neural commonsense knowledge graphs JD Hwang, C Bhagavatula, R Le Bras, J Da, K Sakaguchi, A Bosselut, ... AAAI 2021, 2021 | 358 | 2021 |
| Fast model editing at scale E Mitchell, C Lin, A Bosselut, C Finn, CD Manning ICLR 2022, 2022 | 283 | 2022 |
| Learning to write with cooperative discriminators A Holtzman, J Buys, M Forbes, A Bosselut, D Golub, Y Choi ACL 2018, 2018 | 266 | 2018 |
| GreaseLM: Graph reasoning enhanced language models for question answering X Zhang, A Bosselut, M Yasunaga, H Ren, P Liang, CD Manning, ... ICLR 2022, 2022 | 200 | 2022 |
| Memory-based model editing at scale E Mitchell, C Lin, A Bosselut, CD Manning, C Finn ICML 2022, 2022 | 173 | 2022 |
| Dynamic neuro-symbolic knowledge graph construction for zero-shot commonsense question answering A Bosselut, R Le Bras, Y Choi AAAI 2021, 2021 | 165 | 2021 |
| Deep bidirectional language-knowledge graph pretraining M Yasunaga, A Bosselut, H Ren, X Zhang, CD Manning, PS Liang, ... NeurIPS 2022, 2022 | 153 | 2022 |
| Commonsense knowledge base completion with structural and semantic context C Malaviya, C Bhagavatula, A Bosselut, Y Choi AAAI 2020, 2020 | 147* | 2020 |
| The gem benchmark: Natural language generation, its evaluation and metrics S Gehrmann, T Adewumi, K Aggarwal, PS Ammanamanchi, ... arXiv preprint arXiv:2102.01672, 2021 | 142 | 2021 |
| Counterfactual story reasoning and generation L Qin, A Bosselut, A Holtzman, C Bhagavatula, E Clark, Y Choi EMNLP 2019, 2019 | 135 | 2019 |
| Simulating action dynamics with neural process networks A Bosselut, O Levy, A Holtzman, C Ennis, D Fox, Y Choi ICLR 2018, 2017 | 128 | 2017 |
| Modeling naive psychology of characters in simple commonsense stories H Rashkin, A Bosselut, M Sap, K Knight, Y Choi ACL 2018, 2018 | 101 | 2018 |
| Reasoning about actions and state changes by injecting commonsense knowledge N Tandon, BD Mishra, J Grus, W Yih, A Bosselut, P Clark EMNLP 2018, 2018 | 94 | 2018 |
| Commonsense reasoning for natural language processing M Sap, V Shwartz, A Bosselut, Y Choi, D Roth Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 92 | 2020 |
| Discourse-aware neural rewards for coherent text generation A Bosselut, A Celikyilmaz, X He, J Gao, PS Huang, Y Choi NAACL 2018, 2018 | 90 | 2018 |
| Wiqa: A dataset for" what if..." reasoning over procedural text N Tandon, BD Mishra, K Sakaguchi, A Bosselut, P Clark EMNLP 2019, 2019 | 86 | 2019 |
Yejin ChoiUniversity of Washington / Allen Institute for Artificial Intelligence在 cs.washington.edu 的电子邮件经过验证
