Claudia Shi
CS PhD student at Columbia University
I am broadly interested in machine learning and causal inference. In the past couple of years, I've worked on bringing machine learning insights to causal effect estimation. Recently, I have been thinking about how to ensure large language models produce factual and human-aligned responses. (My hunch: insights from causality can help! )
Aside from my main research, I co-organize the Machine Learning in New York City speaker series and advise AI alignment research projects at FAR AI.
Publications
On the Misspecification of Linear Assumptions in Synthetic Control
Achille Nazaret, Claudia Shi, David M. Blei
arXiv:2302.12777, AISTATS 2024 (ORAL)
Evaluating the Moral Beliefs Encoded in LLMs
Nino Scherrer*, Claudia Shi*, Amir Feder, David Blei (*equal contribution)
NeurIPS 2023 (spotlight)
On the Assumptions of Synthetic Control Methods
Claudia Shi, Dhanya Sridhar, Vishal Misra, David M. Blei
AISTATS 2022 (Oral)
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Stephen Casper, Xander Davies, Claudia Shi, T. Gilbert, J'er'emy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, P. Freire, Tony Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, J. Pfau, Dmitrii Krasheninnikov, Xin Chen, L. Langosco, Peter Hase, Erdem Biyik, A. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
TMLR 2023
Data Augmentations for Improved (Large) Language Model Generalization
Amir Feder, Yoav Wald, Claudia Shi, S. Saria, David Blei
NeurIPS, 2023
An Invariant Learning Characterization of Controlled Text Generation
Carolina Zheng*, Claudia Shi*, Amir Feder, Keyon Vafa, D. Blei (*equal contribution)
ACL, 2023
Conformal Sensitivity Analysis for Individual Treatment Effects
Mingzhang Yin, Claudia Shi, Yixin Wang, D. Blei
Journal of the American Statistical Association, 2021
Invariant Representation Learning for Treatment Effect Estimation
Claudia Shi, Victor Veitch, D. Blei
UAI 2021, 2020
Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi, D. Blei, Victor Veitch
NeurIPS, 2019