| Finetuned language models are zero-shot learners J Wei, M Bosma, VY Zhao, K Guu, AW Yu, B Lester, N Du, AM Dai, QV Le arXiv preprint arXiv:2109.01652, 2021 | 3477 | 2021 |
| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 2562 | 2023 |
| Retrieval augmented language model pre-training K Guu, K Lee, Z Tung, P Pasupat, M Chang International conference on machine learning, 3929-3938, 2020 | 2088 | 2020 |
| Traversing Knowledge Graphs in Vector Space K Guu, J Miller, P Liang Empirical Methods in Natural Language Processing (EMNLP), 2015 | 425 | 2015 |
| Generating Sentences by Editing Prototypes K Guu, TB Hashimoto, Y Oren, P Liang Transactions of the Association for Computational Linguistics 6, 437-450, 2018 | 377 | 2018 |
| Rarr: Researching and revising what language models say, using language models L Gao, Z Dai, P Pasupat, A Chen, AT Chaganty, Y Fan, VY Zhao, N Lao, ... arXiv preprint arXiv:2210.08726, 2022 | 248 | 2022 |
| Promptagator: Few-shot dense retrieval from 8 examples Z Dai, VY Zhao, J Ma, Y Luan, J Ni, J Lu, A Bakalov, K Guu, KB Hall, ... arXiv preprint arXiv:2209.11755, 2022 | 216 | 2022 |
| From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood K Guu, P Pasupat, EZ Liu, P Liang Association for Computational Linguistics (ACL), 2017 | 212 | 2017 |
| Reinforcement learning on web interfaces using workflow-guided exploration EZ Liu, K Guu, P Pasupat, T Shi, P Liang arXiv preprint arXiv:1802.08802, 2018 | 206 | 2018 |
| A Retrieve-and-Edit Framework for Predicting Structured Outputs TB Hashimoto, K Guu, Y Oren, PS Liang Advances in Neural Information Processing Systems, 10073-10083, 2018 | 188 | 2018 |
| Transforming question answering datasets into natural language inference datasets D Demszky, K Guu, P Liang arXiv preprint arXiv:1809.02922, 2018 | 181 | 2018 |
| Pretraining with contrastive sentence objectives improves discourse performance of language models D Iter, K Guu, L Lansing, D Jurafsky arXiv preprint arXiv:2005.10389, 2020 | 88 | 2020 |
| Neurips 2020 efficientqa competition: Systems, analyses and lessons learned S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ... NeurIPS 2020 Competition and Demonstration Track, 86-111, 2021 | 79 | 2021 |
| Towards tracing factual knowledge in language models back to the training data E Akyürek, T Bolukbasi, F Liu, B Xiong, I Tenney, J Andreas, K Guu arXiv preprint arXiv:2205.11482, 2022 | 76 | 2022 |
| Light timeout optimization X Gu, K Gu, D Nulu US Patent 8,538,596, 2013 | 75 | 2013 |
| Unlocking compositional generalization in pre-trained models using intermediate representations J Herzig, P Shaw, MW Chang, K Guu, P Pasupat, Y Zhang arXiv preprint arXiv:2104.07478, 2021 | 72 | 2021 |
| Kermit: Generative insertion-based modeling for sequences W Chan, N Kitaev, K Guu, M Stern, J Uszkoreit arXiv preprint arXiv:1906.01604, 2019 | 72 | 2019 |
| Neural data augmentation via example extrapolation K Lee, K Guu, L He, T Dozat, HW Chung arXiv preprint arXiv:2102.01335, 2021 | 62 | 2021 |
| Dialog inpainting: Turning documents into dialogs Z Dai, AT Chaganty, VY Zhao, A Amini, QM Rashid, M Green, K Guu International conference on machine learning, 4558-4586, 2022 | 61 | 2022 |
| Mapping natural language commands to web elements P Pasupat, TS Jiang, EZ Liu, K Guu, P Liang arXiv preprint arXiv:1808.09132, 2018 | 53 | 2018 |
Panupong PasupatGoogle確認したメール アドレス: cs.stanford.edu