| 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 | 5582 | 2023 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1291 | 2022 |
| 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 | 909 | 2024 |
| Quantifying memorization across neural language models N Carlini, D Ippolito, M Jagielski, K Lee, F Tramer, C Zhang arXiv preprint arXiv:2202.07646, 2022 | 696 | 2022 |
| Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs H Cho, D Ippolito, YW Yu arXiv preprint arXiv:2003.11511, 2020 | 606 | 2020 |
| Extracting training data from diffusion models N Carlini, J Hayes, M Nasr, M Jagielski, V Sehwag, F Tramer, B Balle, ... 32nd USENIX Security Symposium (USENIX Security 23), 5253-5270, 2023 | 599 | 2023 |
| 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 | 587 | 2021 |
| Wordcraft: story writing with large language models A Yuan, A Coenen, E Reif, D Ippolito Proceedings of the 27th International Conference on Intelligent User …, 2022 | 404 | 2022 |
| Automatic detection of generated text is easiest when humans are fooled D Ippolito, D Duckworth, C Callison-Burch, D Eck Proceedings of the Association for Computational Linguistics, 2020 | 383 | 2020 |
| 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 | 281 | 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, 2024 | 267 | 2024 |
| The need for privacy with public digital contact tracing during the COVID-19 pandemic Y Bengio, R Janda, YW Yu, D Ippolito, M Jarvie, D Pilat, B Struck, ... The Lancet Digital Health 2 (7), e342-e344, 2020 | 174 | 2020 |
| A recipe for arbitrary text style transfer with large language models E Reif, D Ippolito, A Yuan, A Coenen, C Callison-Burch, J Wei arXiv preprint arXiv:2109.03910, 2021 | 168 | 2021 |
| 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 | 146 | 2023 |
| Comparison of Diverse Decoding Methods from Conditional Language Models D Ippolito, R Kriz, M Kustikova, J Sedoc, C Callison-Burch Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 144 | 2019 |
| 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 | 139 | 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, ... arXiv preprint arXiv:2305.13169, 2023 | 126 | 2023 |
| Palm: Scaling language modeling with pathways. arXiv 2022 A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311 10, 2022 | 123 | 2022 |
| Creative writing with an ai-powered writing assistant: Perspectives from professional writers D Ippolito, A Yuan, A Coenen, S Burnam arXiv preprint arXiv:2211.05030, 2022 | 106 | 2022 |
| Measuring forgetting of memorized training examples M Jagielski, O Thakkar, F Tramer, D Ippolito, K Lee, N Carlini, E Wallace, ... arXiv preprint arXiv:2207.00099, 2022 | 94 | 2022 |
Chris Callison-BurchProfessor, University of PennsylvaniaVerified email at upenn.edu
