| Lamda: Language models for dialog applications R Thoppilan, D De Freitas, J Hall, N Shazeer, A Kulshreshtha, HT Cheng, ... arXiv preprint arXiv:2201.08239, 2022 | 1204 | 2022 |
| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 824 | 2023 |
| Learning a SAT solver from single-bit supervision D Selsam, M Lamm, B Bünz, P Liang, L de Moura, DL Dill arXiv preprint arXiv:1802.03685, 2018 | 475 | 2018 |
| Measuring attribution in natural language generation models H Rashkin, V Nikolaev, M Lamm, L Aroyo, M Collins, D Das, S Petrov, ... Computational Linguistics 49 (4), 777-840, 2023 | 107 | 2023 |
| Decontextualization: Making sentences stand-alone E Choi, J Palomaki, M Lamm, T Kwiatkowski, D Das, M Collins Transactions of the Association for Computational Linguistics 9, 447-461, 2021 | 79 | 2021 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 76 | 2024 |
| Qed: A framework and dataset for explanations in question answering M Lamm, J Palomaki, C Alberti, D Andor, E Choi, LB Soares, M Collins Transactions of the Association for computational Linguistics 9, 790-806, 2021 | 67 | 2021 |
| Compositional generalization in image captioning M Nikolaus, M Abdou, M Lamm, R Aralikatte, D Elliott arXiv preprint arXiv:1909.04402, 2019 | 48 | 2019 |
| Retrieval-guided counterfactual generation for QA B Paranjape, M Lamm, I Tenney arXiv preprint arXiv:2110.07596, 2021 | 25 | 2021 |
| Graph neural networks and boolean satisfiability B Bünz, M Lamm arXiv preprint arXiv:1702.03592, 2017 | 23 | 2017 |
| Textual analogy parsing: What's shared and what's compared among analogous facts M Lamm, AT Chaganty, CD Manning, D Jurafsky, P Liang arXiv preprint arXiv:1809.02700, 2018 | 22 | 2018 |
| TinkerBell: Cross-lingual Cold-Start Knowledge Base Construction. M Al-Badrashiny, J Bolton, AT Chaganty, K Clark, C Harman, L Huang, ... TAC, 2017 | 18 | 2017 |
| Gapping constructions in universal dependencies v2 S Schuster, M Lamm, CD Manning Proceedings of the NoDaLiDa 2017 workshop on Universal Dependencies (UDW …, 2017 | 16 | 2017 |
| Ellipsis resolution as question answering: An evaluation R Aralikatte, M Lamm, D Hardt, A Søgaard arXiv preprint arXiv:1908.11141, 2019 | 14 | 2019 |
| Qsrl: A semantic role-labeling schema for quantitative facts M Lamm, A Chaganty, D Jurafsky, CD Manning, P Liang The First Financial Narrative Processing Workshop (FNP 2018) 44, 2018 | 10 | 2018 |
| Stanford at TAC KBP 2017: Building a Trilingual Relational Knowledge Graph. AT Chaganty, A Paranjape, J Bolton, M Lamm, J Lei, A See, K Clark, ... TAC, 2017 | 6 | 2017 |
| Ellipsis and coreference resolution as question answering R Aralikatte, M Lamm, D Hardt, A Søgaard | 5 | 2019 |
| QED: A Linguistically Principled Framework for Explainable Question Answering M Lamm, J Palomaki, C Alberti, D Andor, LB Soares, M Collins | | 2021 |
| A Simple Transfer Learning Baseline for Ellipsis Resolution R Aralikatte, M Lamm, D Hardt, A Søgaard arXiv preprint arXiv:1908.11141, 2019 | | 2019 |
| The Pragmatics of Indirect Commands in Collaborative Discourse M Lamm, M Eric arXiv preprint arXiv:1705.03454, 2017 | | 2017 |
Percy LiangAssociate Professor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
