(she/her)
Hello!
I’m currently a Research Engineer at Google Brain and a PhD student at Cornell advised by David Mimno.
Specifically, I study security and privacy in large language models.
I’m broadly interested in the translation between people and the systems we build. What kinds of decisions can algorithms help with, and which should we leave algorithms out of? What kinds of objectives, political or social, can we, or can we not write down?
Before that, I had great fun learning about how real neural networks (brains!) take in the world with Jonathan Pillow and Uri Hasson during my undergrad in Operations Research at Princeton.
You can find me on the internet: Twitter, Google Scholar, Goodreads
Apply to work with me
Publications
- Quantifying Memorization Across Neural Language Models [arxiv]
- Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang. Feb 2022
- What Does it Mean for a Language Model to Preserve Privacy? [arxiv]
- Hannah Brown, Katherine Lee, Fatemehsadat Mireshghalla, Reza Shokri, Florian Tramèr. Feb 2022
- Counterfactual Memorization in Neural Language Models [arxiv]
- Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini. December 2021
- Deduplicating Training Data Makes Language Models Better [arxiv]
- Katherine Lee*, Daphne Ippolito*, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini. July 2021
- Extracting Training Data from Large Language Models [arxiv] [blog]
- Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, Alina Oprea, Colin Raffel. Dec, 2020
- WT5?! Training Text-to-Text Models to Explain their Predictions [arxiv]
- Sharan Narang, Colin Raffel, Katherine Lee, Adam Roberts, Noah Fiedel, Karishma Malkan. April, 2020
- T5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer [JMLR]
- Colin Raffel*, Noam Shazeer*, Adam Roberts*, Katherine Lee*, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu. June, 2020
- Hallucinations in Neural Machine Translation [NeurIPS IRASL]
- Katherine Lee, Orhan Firat, Ashish Agarwal, Clara Fannjiang, and David Sussillo. Dec, 2018
- Propagation of information along the cortical hierarchy as a function of attention while reading and listening to stories [Cerebral Cortex]
- Mor Regev, Erez Simony, Katherine Lee, Kean Ming Tan, Janice Chen, Uri Hasson. Sep, 2019
Writing
Writing a Google AI Residency Cover letter with Ben Eysenbach (2019)
Submit to Journals [pdf] (2018)
Fun writing
Sourdough Literature Review (2020)
Talks
- Memorization in Language Models [slides] [poster]
- University of Toronto, May 2022
- Mosaic ML, Jul 2022
- GovAI, Aug 2022
- ML Security & Privacy Seminar, Aug 2022
- LEgally Attentive Data Scientists, Sep 2022
- Cornell, NLP Seminar, Sep 2022
- Cornell, C-Psyd, Sep, 2022
- What does Privacy in Language Modeling Mean? [slides]
- UNC, Apr 2022
- Cornell, April 2022
Service
- Helped organize WELM workshop at ICLR 2021 and moderated a panel discussion on “Bias, safety, copyright, and efficiency”
- Reviewer for NeurIPS, ICML.
Fun!
In my free time, I enjoy making stuff. Sometimes this is pottery, sourdough, or knitting/crocheting. I also enjoy being outdoors, listening to jazz, and dancing. Sometimes all at the same time! I used to live here
In the more distant past, I’ve also solved for optimal seating arrangements at Google, and I spotted ships at bay with hyperspectral sensors at the Naval Research Lab in DC.
