Aaron Schein

33 papers A* 6A 3B 1Journal 16Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Layers at Similar Depths Generate Similar Activations Across LLM Architectures.
CoRR
Christopher Wolfram, Aaron Schein
2025 A* conf
Linear Representations of Political Perspective Emerge in Large Language Models.
ICLR
Junsol Kim, James Evans, Aaron Schein
2025 J jnl
Linear Representations of Political Perspective Emerge in Large Language Models.
CoRR
Junsol Kim, James Evans, Aaron Schein
2024 — conf
Activation Scaling for Steering and Interpreting Language Models.
EMNLP (Findings)
Niklas Stoehr, Kevin Du, Vésteinn Snæbjarnarson, Robert West, Ryan Cotterell, Aaron Schein
2024 J jnl
Activation Scaling for Steering and Interpreting Language Models.
CoRR
Niklas Stoehr, Kevin Du, Vésteinn Snæbjarnarson, Robert West, Ryan Cotterell, Aaron Schein
2024 J jnl
Addressing Discretization-Induced Bias in Demographic Prediction.
CoRR
Evan Dong, Aaron Schein, Yixin Wang, Nikhil Garg
2024 — conf
Context versus Prior Knowledge in Language Models.
ACL (1)
Kevin Du, Vésteinn Snæbjarnarson, Niklas Stoehr, Jennifer C. White, Aaron Schein, Ryan Cotterell
2024 J jnl
Context versus Prior Knowledge in Language Models.
CoRR
Kevin Du, Vésteinn Snæbjarnarson, Niklas Stoehr, Jennifer C. White, Aaron Schein, Ryan Cotterell
2024 J jnl
Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data.
CoRR
Anjali Nagulpally, Patrick Flaherty, Aaron Schein
2023 — conf
An Ordinal Latent Variable Model of Conflict Intensity.
ACL (1)
Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West, Ryan Cotterell, Aaron Schein
2023 J jnl
Measurement in the Age of LLMs: An Application to Ideological Scaling.
CoRR
Sean O'Hagan, Aaron Schein
2023 A conf
Sentiment as an Ordinal Latent Variable.
EACL
Niklas Stoehr, Ryan Cotterell, Aaron Schein
2023 A conf
The Ordered Matrix Dirichlet for State-Space Models.
AISTATS
Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein
2022 J jnl
An Ordinal Latent Variable Model of Conflict Intensity.
CoRR
Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West, Ryan Cotterell, Aaron Schein
2022 — ed.
Proceedings on "I Can't Believe It's Not Better! - Understanding Deep Learning Through Empirical Falsification" at NeurIPS 2022 Workshops, 03 December 2022, New Orleans, Louisiana, USA
ICBINB
Javier Antorán, Arno Blaas, Fan Feng, Sahra Ghalebikesabi, Ian Mason, Melanie F. Pradier, David Rohde, Francisco J. R. Ruiz, Aaron Schein
2022 J jnl
The Ordered Matrix Dirichlet for Modeling Ordinal Dynamics.
CoRR
Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein
2021 A* conf
Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections.
WWW
Aaron Schein, Keyon Vafa, Dhanya Sridhar, Victor Veitch, Jeffrey Quinn, James Moffet, David M. Blei, Donald P. Green
2021 J jnl
Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data.
CoRR
Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty
2021 A conf
Doubly non-central beta matrix factorization for DNA methylation data.
UAI
Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty
2021 — ed.
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, Virtual Workshop, December 13, 2021.
ICBINB@NeurIPS
Melanie F. Pradier, Aaron Schein, Stephanie L. Hyland, Francisco J. R. Ruiz, Jessica Zosa Forde
2020 — ed.
"I Can't Believe It's Not Better!" at NeurIPS Workshops, Virtual, December 12, 2020
ICBINB@NeurIPS
Jessica Zosa Forde, Francisco J. R. Ruiz, Melanie F. Pradier, Aaron Schein
2019 A* conf
Locally Private Bayesian Inference for Count Models.
ICML
Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach
2019 A* conf
Poisson-Randomized Gamma Dynamical Systems.
NeurIPS
Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2019 J jnl
Poisson-Randomized Gamma Dynamical Systems.
CoRR
Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2018 J jnl
Locally Private Bayesian Inference for Count Models.
CoRR
Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach
2017 J jnl
Poisson-Gamma Dynamical Systems.
CoRR
Aaron Schein, Mingyuan Zhou, Hanna M. Wallach
2016 A* conf
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations.
ICML
Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2016 J jnl
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations.
CoRR
Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2016 — conf
Poisson-Gamma dynamical systems.
NIPS
Aaron Schein, Hanna M. Wallach, Mingyuan Zhou
2015 A* conf
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts.
KDD
Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
2015 J jnl
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts.
CoRR
Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
2013 J jnl
Inferring Multilateral Relations from Dynamic Pairwise Interactions.
CoRR
Aaron Schein, Juston Moore, Hanna M. Wallach
2012 B conf
International Multicultural Name Matching Competition: Design, Execution, Results, and Lessons Learned.
LREC
Keith J. Miller, Elizabeth Schroeder Richerson, Sarah McLeod, James Finley, Aaron Schein