Katherine Lee

Orcid: 0000-0002-9537-6195

According to our database1, Katherine Lee authored at least 27 papers between 2004 and 2024.

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Bibliography

2024
An Abundance of Katherines: The Game Theory of Baby Naming.
CoRR, 2024

Stealing Part of a Production Language Model.
CoRR, 2024

Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain (The Short Version).
Proceedings of the Symposium on Computer Science and Law, 2024

Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
PaLM: Scaling Language Modeling with Pathways.
J. Mach. Learn. Res., 2023

Scalable Extraction of Training Data from (Production) Language Models.
CoRR, 2023

Report of the 1st Workshop on Generative AI and Law.
CoRR, 2023

Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain.
CoRR, 2023

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset.
CoRR, 2023

Are aligned neural networks adversarially aligned?
CoRR, 2023

A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity.
CoRR, 2023

Students Parrot Their Teachers: Membership Inference on Model Distillation.
CoRR, 2023

Counterfactual Memorization in Neural Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Students Parrot Their Teachers: Membership Inference on Model Distillation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy.
Proceedings of the 16th International Natural Language Generation Conference, 2023

Reverse-Engineering Decoding Strategies Given Blackbox Access to a Language Generation System.
Proceedings of the 16th International Natural Language Generation Conference, 2023

Measuring Forgetting of Memorized Training Examples.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Quantifying Memorization Across Neural Language Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy.
CoRR, 2022

What Does it Mean for a Language Model to Preserve Privacy?
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Deduplicating Training Data Makes Language Models Better.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Extracting Training Data from Large Language Models.
Proceedings of the 30th USENIX Security Symposium, 2021

Predictive Modeling of Healthcare Utilization Metrics Identifies Adult Patients at High Risk for Suicide Attempt in the Primary Care Setting.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.
J. Mach. Learn. Res., 2020

WT5?! Training Text-to-Text Models to Explain their Predictions.
CoRR, 2020

2015
A computer-aided diagnosis system to identify regions of pathologic change in temporal subtraction images of the chest.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

2004
Analysis and Detection of Reading Miscues for Interactive Literacy Tutors.
Proceedings of the COLING 2004, 2004


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