Skip to content

Victor Veitch

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

14

Venues

6

Active years

2019–2025

Best venue rank

A*

Where they publish

Papers

14 indexed papers, newest first.

YearVenueTitleAuthors
2025ICLRThe Geometry of Categorical and Hierarchical Concepts in Large Language Models.Kiho Park, Yo Joong Choe, Yibo Jiang, Victor Veitch
2025ICMLRATE: Causal Explainability of Reward Models with Imperfect Counterfactuals.David Reber, Sean M. Richardson, Todd Nief, Cristina Garbacea, Victor Veitch
2024ICMLOn the Origins of Linear Representations in Large Language Models.Yibo Jiang, Goutham Rajendran, Pradeep Kumar Ravikumar, Bryon Aragam, Victor Veitch
2024ICMLThe Linear Representation Hypothesis and the Geometry of Large Language Models.Kiho Park, Yo Joong Choe, Victor Veitch
2024ICMLTransforming and Combining Rewards for Aligning Large Language Models.Zihao Wang, Chirag Nagpal, Jonathan Berant, Jacob Eisenstein, Alexander Nicholas D'Amour, Sanmi Koyejo, Victor Veitch
2023ICLRCausal Estimation for Text Data with (Apparent) Overlap Violations.Lin Gui, Victor Veitch
2023ICLREfficient Conditionally Invariant Representation Learning.Roman Pogodin, Namrata Deka, Yazhe Li, Danica J. Sutherland, Victor Veitch, Arthur Gretton
2021ICMLValid Causal Inference with (Some) Invalid Instruments.Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
2021NAACLCausal Effects of Linguistic Properties.Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar
2021WWWAssessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections.Aaron Schein, Keyon Vafa, Dhanya Sridhar, Victor Veitch, Jeffrey Quinn, James Moffet, David M. Blei, Donald P. Green
2021UAIInvariant representation learning for treatment effect estimation.Claudia Shi, Victor Veitch, David M. Blei
2020UAIAdapting Text Embeddings for Causal Inference.Victor Veitch, Dhanya Sridhar, David M. Blei
2019AISTATSEmpirical Risk Minimization and Stochastic Gradient Descent for Relational Data.Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz
2019ICLRNon-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach.Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz