Ippolito, Daphne

PaLM: Scaling Language Modeling with Pathways

Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,590

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

Wordcraft: Story Writing With Large Language Models

Yuan, A., Coenen, A., Reif, E., & Ippolito, D. (2022) · 27th International Conference on Intelligent User Interfaces

Artificial Intelligence in GamesInnovative Human-Technology Interaction

Cited by 374

Deduplicating Training Data Makes Language Models Better

Lee, K., Ippolito, D., Nystrom, A., Zhang, C., Eck, D., Callison-Burch, C., & Carlini, N. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 304

Gemma: Open Models Based on Gemini Research and Technology

Gemma Team, Mesnard, T., Hardin, C., Dadashi, R., Bhupatiraju, S., Pathak, S., Sifre, L., Rivière, M., Kale, M. S., Love, J., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 284

Automatic Detection of Generated Text is Easiest when Humans are Fooled

Ippolito, D., Duckworth, D., Callison-Burch, C., & Eck, D. (2019) · arXiv

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 264

Automatic Detection of Generated Text is Easiest when Humans are Fooled

Ippolito, D., Duckworth, D., Callison-Burch, C., & Eck, D. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 264

Quantifying Memorization Across Neural Language Models

Carlini, N., Ippolito, D., Jagielski, M., Lee, K., Tramer, F., & Zhang, C. (2022) · arXiv

Topic ModelingPrivacy-Preserving Technologies in Data

Cited by 204

Scalable Extraction of Training Data from (Production) Language Models

Nasr, M., Carlini, N., Hayase, J., Jagielski, M., Cooper, A. F., Ippolito, D., Choquette-Choo, C. A., Wallace, E., Tramèr, F., & Lee, K. (2023) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 96

Real or fake text?: Investigating human ability to detect boundaries between human-written and machine-generated text

Dugan, L., Ippolito, D., Kirubarajan, A., Shi, S., & Callison-Burch, C. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 54

Counterfactual Memorization in Neural Language Models

Zhang, C., Ippolito, D., Lee, K., Jagielski, M., Tramèr, F., & Carlini, N. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 54

Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers

Ippolito, D., Yuan, A., Coenen, A., & Burnam, S. (2022) · arXiv

Artificial Intelligence in GamesNatural Language Processing Techniques

Cited by 52

RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors

Dugan, L., Hwang, A., Trhlík, F., Zhu, A., Ludan, J. M., Xu, H., Ippolito, D., & Callison-Burch, C. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Authorship Attribution and ProfilingNatural Language Processing Techniques

Cited by 48

Wordcraft: a Human-AI Collaborative Editor for Story Writing

Coenen, A., Davis, L., Ippolito, D., Reif, E., & Yuan, A. (2021) · arXiv

Speech and dialogue systemsArtificial Intelligence in Games

Cited by 35

Preventing generation of verbatim memorization in language models gives a false sense of privacy

Ippolito, D., Tramer, F., Nasr, M., Zhang, C., Jagielski, M., Lee, K., Choquette Choo, C., & Carlini, N. (2023) · Proceedings of the 16th International Natural Language Generation Conference

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 28

Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards

Huang, Y., Nasr, M., Angelopoulos, A., Carlini, N., Chiang, W.-L., Choquette-Choo, C. A., Ippolito, D., Jagielski, M., Lee, K., Liu, K. Z., et al. (2025) · arXiv

Adversarial Robustness in Machine LearningSpam and Phishing Detection

Cited by 17

Deduplicating Training Data Makes Language Models Better

Lee, K., Ippolito, D., Nystrom, A., Zhang, C., Eck, D., Callison-Burch, C., & Carlini, N. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 11

Noveltybench: Evaluating language models for humanlike diversity

Zhang, Y., Diddee, H., Holm, S., Liu, H., Liu, X., Samuel, V., Wang, B., & Ippolito, D. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors

Dugan, L., Hwang, A., Trhlik, F., Ludan, J. M., Zhu, A., Xu, H., Ippolito, D., & Callison-Burch, C. (2024) · arXiv

Authorship Attribution and ProfilingAdversarial Robustness in Machine Learning

Cited by 1

Forcing diffuse distributions out of language models

Zhang, Y., Schwarzschild, A., Carlini, N., Kolter, Z., & Ippolito, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0