| Electra: Pre-training text encoders as discriminators rather than generators K Clark, MT Luong, QV Le, CD Manning arXiv preprint arXiv:2003.10555, 2020 | 3141 | 2020 |
| What does bert look at? an analysis of bert's attention K Clark, U Khandelwal, O Levy, CD Manning arXiv preprint arXiv:1906.04341, 2019 | 1409 | 2019 |
| Deep reinforcement learning for mention-ranking coreference models K Clark, CD Manning arXiv preprint arXiv:1609.08667, 2016 | 465 | 2016 |
| Semi-Supervised Sequence Modeling with Cross-View Training K Clark, MT Luong, CD Manning, QV Le arXiv preprint arXiv:1809.08370, 2018 | 420 | 2018 |
| Improving coreference resolution by learning entity-level distributed representations K Clark, CD Manning arXiv preprint arXiv:1606.01323, 2016 | 411 | 2016 |
| Inducing domain-specific sentiment lexicons from unlabeled corpora WL Hamilton, K Clark, J Leskovec, D Jurafsky Proceedings of the conference on empirical methods in natural language …, 2016 | 404 | 2016 |
| Large-scale analysis of counseling conversations: An application of natural language processing to mental health T Althoff, K Clark, J Leskovec Transactions of the Association for Computational Linguistics 4, 463-476, 2016 | 303 | 2016 |
| Emergent linguistic structure in artificial neural networks trained by self-supervision CD Manning, K Clark, J Hewitt, U Khandelwal, O Levy Proceedings of the National Academy of Sciences 117 (48), 30046-30054, 2020 | 265 | 2020 |
| Entity-centric coreference resolution with model stacking K Clark, CD Manning Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 259 | 2015 |
| Bam! born-again multi-task networks for natural language understanding K Clark, MT Luong, U Khandelwal, CD Manning, QV Le arXiv preprint arXiv:1907.04829, 2019 | 203 | 2019 |
| Towards expert-level medical question answering with large language models K Singhal, T Tu, J Gottweis, R Sayres, E Wulczyn, L Hou, K Clark, S Pfohl, ... arXiv preprint arXiv:2305.09617, 2023 | 99 | 2023 |
| Sample efficient text summarization using a single pre-trained transformer U Khandelwal, K Clark, D Jurafsky, L Kaiser arXiv preprint arXiv:1905.08836, 2019 | 80 | 2019 |
| Electra: Pre-training text encoders as discriminators rather than generators. arXiv 2020 K Clark, MT Luong, QV Le, CD Manning arXiv preprint arXiv:2003.10555, 2020 | 68 | 2020 |
| Revminer: An extractive interface for navigating reviews on a smartphone J Huang, O Etzioni, L Zettlemoyer, K Clark, C Lee Proceedings of the 25th annual ACM symposium on User interface software and …, 2012 | 68 | 2012 |
| Pre-training transformers as energy-based cloze models K Clark, MT Luong, QV Le, CD Manning arXiv preprint arXiv:2012.08561, 2020 | 67 | 2020 |
| Text-to-image diffusion models are zero-shot classifiers K Clark, P Jaini arXiv preprint arXiv:2303.15233, 2023 | 12 | 2023 |
| 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 |
| Directly fine-tuning diffusion models on differentiable rewards K Clark, P Vicol, K Swersky, DJ Fleet arXiv preprint arXiv:2309.17400, 2023 | 3 | 2023 |
| Meta-Learning Fast Weight Language Models K Clark, K Guu, MW Chang, P Pasupat, G Hinton, M Norouzi arXiv preprint arXiv:2212.02475, 2022 | 3 | 2022 |
| Intriguing properties of generative classifiers P Jaini, K Clark, R Geirhos arXiv preprint arXiv:2309.16779, 2023 | 2 | 2023 |
Christopher D ManningProfessor of Computer Science and Linguistics, Stanford University在 stanford.edu 的电子邮件经过验证
