| Exploring the limits of transfer learning with a unified text-to-text transformer C Raffel, N Shazeer, A Roberts, K Lee, S Narang, M Matena, Y Zhou, W Li, ... The Journal of Machine Learning Research 21 (1), 5485-5551, 2020 | 21934 | 2020 |
| Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... Journal of Machine Learning Research 24 (240), 1-113, 2023 | 5867 | 2023 |
| 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 | 3405 | 2023 |
| Extracting Training Data from Large Language Models. N Carlini, F Tramer, E Wallace, M Jagielski, A Herbert-Voss, K Lee, ... USENIX Security Symposium 6, 2021 | 2052 | 2021 |
| PaLM 2 Technical Report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1617 | 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 | 1255 | 2024 |
| Gemma: Open models based on gemini research and technology G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ... arXiv preprint arXiv:2403.08295, 2024 | 1100 | 2024 |
| Quantifying memorization across neural language models N Carlini, D Ippolito, M Jagielski, K Lee, F Tramer, C Zhang The Eleventh International Conference on Learning Representations, 2022 | 715 | 2022 |
| Deduplicating training data makes language models better K Lee, D Ippolito, A Nystrom, C Zhang, D Eck, C Callison-Burch, N Carlini arXiv preprint arXiv:2107.06499, 2021 | 624 | 2021 |
| Scalable Extraction of Training Data from (Production) Language Models M Nasr, N Carlini, J Hayase, M Jagielski, AF Cooper, D Ippolito, ... arXiv preprint arXiv:2311.17035, 2023 | 321 | 2023 |
| Are aligned neural networks adversarially aligned? N Carlini, M Nasr, CA Choquette-Choo, M Jagielski, I Gao, PWW Koh, ... Advances in Neural Information Processing Systems 36, 61478-61500, 2023 | 286 | 2023 |
| What Does it Mean for a Language Model to Preserve Privacy? H Brown, K Lee, F Mireshghallah, R Shokri, F Tramèr 2022 ACM Conference on Fairness, Accountability, and Transparency, 2280-2292, 2022 | 259 | 2022 |
| WT5?! Training Text-to-Text Models to Explain their Predictions S Narang, C Raffel, K Lee, A Roberts, N Fiedel, K Malkan arXiv preprint arXiv:2004.14546, 2020 | 211 | 2020 |
| Counterfactual memorization in neural language models C Zhang, D Ippolito, K Lee, M Jagielski, F Tramèr, N Carlini Advances in Neural Information Processing Systems 36, 39321-39362, 2023 | 159 | 2023 |
| Hallucinations in neural machine translation K Lee, O Firat, A Agarwal, C Fannjiang, D Sussillo | 157 | 2018 |
| Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski, K Lee, ... arXiv preprint arXiv:2210.17546, 2022 | 151 | 2022 |
| A pretrainer’s guide to training data: Measuring the effects of data age, domain coverage, quality, & toxicity S Longpre, G Yauney, E Reif, K Lee, A Roberts, B Zoph, D Zhou, J Wei, ... Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | 146 | 2024 |
| Palm: Scaling language modeling with pathways, 2022 A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311, 2022 | 137 | 2022 |
| Madlad-400: A multilingual and document-level large audited dataset S Kudugunta, I Caswell, B Zhang, X Garcia, D Xin, A Kusupati, R Stella, ... Advances in Neural Information Processing Systems 36, 67284-67296, 2023 | 111 | 2023 |
| Measuring Forgetting of Memorized Training Examples M Jagielski, O Thakkar, F Tramèr, D Ippolito, K Lee, N Carlini, E Wallace, ... arXiv preprint arXiv:2207.00099, 2022 | 106 | 2022 |
Adam RobertsGoogle DeepMindEmail yang diverifikasi di google.com