| 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 | 4407 | 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 | 983 | 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 | 591 | 2020 |
| Quantifying memorization across neural language models N Carlini, D Ippolito, M Jagielski, K Lee, F Tramer, C Zhang arXiv preprint arXiv:2202.07646, 2022 | 526 | 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 | 458 | 2021 |
| 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 | 438 | 2023 |
| 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 | 388 | 2024 |
| 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 | 328 | 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 | 322 | 2020 |
| 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 | 173 | 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 | 167 | 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 | 163 | 2023 |
| 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 | 148 | 2021 |
| 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 | 129 | 2019 |
| 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 | 112 | 2023 |
| 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 | 105 | 2022 |
| 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 | 98 | 2022 |
| Chateval: A tool for chatbot evaluation J Sedoc, D Ippolito, A Kirubarajan, J Thirani, L Ungar, C Callison-Burch Proceedings of the 2019 conference of the North American chapter of the …, 2019 | 86 | 2019 |
| 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 | 81 | 2022 |
| Trading off diversity and quality in natural language generation H Zhang, D Duckworth, D Ippolito, A Neelakantan arXiv preprint arXiv:2004.10450, 2020 | 78 | 2020 |
Chris Callison-BurchProfessor, University of PennsylvaniaEmail verificata su upenn.edu
