Daphne Ippolito
I'm a senior research scientist at Google Brain. I work on understanding the limitations of neural language models, including their propensity for memorizing their training data. I also work on using natural language generation systems to build tools for creative writing. I received my PhD in 2022 from University of Pennsylvania, and I will be starting as an assistant professor at Carnegie Mellon University in fall 2023.
Authored Publications
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Deduplicating Training Data Makes Language Models Better
Andrew Nystrom
Chiyuan Zhang
Chris Callison-Burch
Katherine Lee
Nicholas Carlini
(2022) (to appear)
Dungeons and Dragons as a Challenge Problem for Artificial Intelligence
Chris Callison-Burch
Lara Martin
NAACL Wordplay Workshop, ACL (2022) (to appear)
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Hyung Won Chung
Sebastian Gehrmann
Parker Schuh
Sasha Tsvyashchenko
Abhishek Rao
Yi Tay
Noam Shazeer
Nan Du
Reiner Pope
James Bradbury
Guy Gur-Ari
Toju Duke
Henryk Michalewski
Xavier Garcia
Liam Fedus
David Luan
Barret Zoph
Ryan Sepassi
David Dohan
Shivani Agrawal
Mark Omernick
Marie Pellat
Aitor Lewkowycz
Erica Moreira
Rewon Child
Oleksandr Polozov
Katherine Lee
Zongwei Zhou
Brennan Saeta
Michele Catasta
Jason Wei
Kathy Meier-Hellstern
arxiv:2204.02311 (2022)
Automatic Detection of Generated Text is Easiest when Humans are Fooled
Chris Callison-Burch
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020), pp. 1808-1822
Towards Better Storylines with Sentence-Level Language Models
David Grangier
Chris Callison-Burch
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020), pp. 1808-1822
Unsupervised Hierarchical Story Infilling
David Grangier
Chris Callison-Burch
NAACL 2019 Workshop on Narrative Understanding, Minneapolis, MN (2019)
