| Chain of thought prompting elicits reasoning in large language models J Wei, X Wang, D Schuurmans, M Bosma, E Chi, Q Le, D Zhou Advances in Neural Information Processing Systems (NeurIPS), 2022 | 12897 | 2022 |
| PaLM: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... Journal of Machine Learning Research (JMLR), 2023 | 5872 | 2023 |
| Learning with Local and Global Consistency D Zhou, O Bousquet, TN Lal, J Weston, B Schölkopf Advances in Neural Information Processing Systems (NeurIPS), 2003 | 5649 | 2003 |
| Emergent abilities of large language models J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ... Transactions on Machine Learning Research (TMLR), 2022 | 3666* | 2022 |
| Scaling instruction-finetuned language models HW Chung, L Hou, S Longpre, B Zoph, Y Tay, W Fedus, Y Li, X Wang, ... Journal of Machine Learning Research (JMLR), 2023 | 3613 | 2023 |
| Self-consistency improves chain of thought reasoning in language models X Wang, J Wei, D Schuurmans, Q Le, E Chi, D Zhou International Conference on Learning Representations (ICLR), 2023 | 2477* | 2023 |
| Recommender systems with social regularization H Ma, D Zhou, C Liu, MR Lyu, I King ACM International Conference on Web Search and Data Mining (WSDM), 2011 | 2143 | 2011 |
| Learning with hypergraphs: Clustering, classification, and embedding D Zhou, J Huang, B Schölkopf Advances in Neural Information Processing Systems (NeurIPS), 2007 | 1778 | 2007 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1648 | 2023 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 1358 | 2024 |
| Least-to-Most Prompting Enables Complex Reasoning in Large Language Models D Zhou, N Schärli, L Hou, J Wei, N Scales, X Wang, D Schuurmans, ... International Conference on Learning Representations (ICLR), 2023 | 1341 | 2023 |
| Ranking on data manifolds D Zhou, J Weston, A Gretton, O Bousquet, B Schölkopf Advances in Neural Information Processing Systems (NeurIPS), 2003 | 1020 | 2003 |
| MobileBERT: a compact task-agnostic BERT for resource-limited devices Z Sun, H Yu, X Song, R Liu, Y Yang, D Zhou Annual Meeting of the Association for Computational Linguistics (ACL), 2020 | 905 | 2020 |
| H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. Self-consistency improves chain of thought reasoning in language models X Wang, J Wei, D Schuurmans, QV Le The Eleventh International Conference on Learning Representations 1, 2023 | 775 | 2023 |
| Semi-supervised graph-based hyperspectral image classification G Camps-Valls, TVB Marsheva, D Zhou IEEE transactions on Geoscience and Remote Sensing 45 (10), 3044-3054, 2007 | 754 | 2007 |
| Large language models as optimizers C Yang, X Wang, Y Lu, H Liu, QV Le, D Zhou, X Chen International Conference on Learning Representations (ICLR), 2024 | 738 | 2024 |
| The flan collection: Designing data and methods for effective instruction tuning S Longpre, L Hou, T Vu, A Webson, HW Chung, Y Tay, D Zhou, QV Le, ... International Conference on Machine Learning (ICML), 2023 | 721 | 2023 |
| Challenging big-bench tasks and whether chain-of-thought can solve them M Suzgun, N Scales, N Schärli, S Gehrmann, Y Tay, HW Chung, ... arXiv preprint arXiv:2210.09261, 2022 | 679 | 2022 |
| Teaching large language models to self-debug X Chen, M Lin, N Schärli, D Zhou International Conference on Learning Representations (ICLR), 2024 | 589 | 2024 |
| Learning from labeled and unlabeled data on a directed graph D Zhou, J Huang, B Schölkopf International conference on Machine learning (ICML), 2005 | 566 | 2005 |
Jason WeiOpenAIVerified email at google.com
