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Hypothesis Testing the Circuit Hypothesis in LLMs
Claudia Shi*, Nicolas Beltran-Velez*, Achille Nazaret*, Carolina Zheng, Adria Garriga-Alonso, Andrew Jesson, Maggie Makar, David Blei
NeurIPS 2024
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On the Misspecification of Linear Assumptions in Synthetic Control
Achille Nazaret, Claudia Shi, David M. Blei
AISTATS 2024 (Oral)
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Evaluating the Moral Beliefs Encoded in LLMs
Nino Scherrer*, Claudia Shi*, Amir Feder, David Blei
NeurIPS 2023 (Spotlight)
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Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Stephen Casper, Xander Davies, Claudia Shi, Thomas Gilbert, Jeremy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro 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, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
TMLR 2023
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Data Augmentations for Improved (Large) Language Model Generalization
Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David Blei
NeurIPS 2023
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An Invariant Learning Characterization of Controlled Text Generation
Carolina Zheng*, Claudia Shi*, Amir Feder, Keyon Vafa, David Blei
ACL 2023
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On the Assumptions of Synthetic Control Methods
Claudia Shi, Dhanya Sridhar, Vishal Misra, David M. Blei
AISTATS 2022 (Oral)
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Conformal Sensitivity Analysis for Individual Treatment Effects
Mingzhang Yin, Claudia Shi, Yixin Wang, David Blei
Journal of the American Statistical Association, 2021
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Invariant Representation Learning for Treatment Effect Estimation
Claudia Shi, Victor Veitch, David Blei
UAI 2021
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Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi, David Blei, Victor Veitch
NeurIPS 2019