Grosse, Roger Baker

15 publications

NeurIPS 2025 Better Training Data Attribution via Better Inverse Hessian-Vector Products Andrew Wang, Elisa Nguyen, Runshi Yang, Juhan Bae, Sheila A. McIlraith, Roger Baker Grosse

NeurIPS 2025 Distributional Training Data Attribution: What Do Influence Functions Sample? Bruno Kacper Mlodozeniec, Isaac Reid, Samuel Power, David Krueger, Murat A Erdogdu, Richard E. Turner, Roger Baker Grosse

NeurIPS 2025 Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference Stephen Zhao, Aidan Li, Rob Brekelmans, Roger Baker Grosse

NeurIPS 2025 What Is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Youngseog Chung, Adithya Pratapa, Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff Schneider, Eduard Hovy, Roger Baker Grosse, Eric P. Xing

NeurIPS 2024 Many-Shot Jailbreaking Cem Anil, Esin Durmus, Nina Panickssery, Mrinank Sharma, Joe Benton, Sandipan Kundu, Joshua Batson, Meg Tong, Jesse Mu, Daniel Ford, Fracesco Mosconi, Rajashree Agrawal, Rylan Schaeffer, Naomi Bashkansky, Samuel Svenningsen, Mike Lambert, Ansh Radhakrishnan, Carson Denison, Evan J Hubinger, Yuntao Bai, Trenton Bricken, Timothy Maxwell, Nicholas Schiefer, James Sully, Alex Tamkin, Tamera Lanhan, Karina Nguyen, Tomasz Korbak, Jared Kaplan, Deep Ganguli, Samuel R. Bowman, Ethan Perez, Roger Baker Grosse, David Duvenaud

ICML 2024 Measuring Stochastic Data Complexity with Boltzmann Influence Functions Nathan Hoyen Ng, Roger Baker Grosse, Marzyeh Ghassemi

ICML 2024 Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger Baker Grosse

ICLR 2024 REFACTOR: Learning to Extract Theorems from Proofs Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger Baker Grosse

ICMLW 2023 Calibrating Language Models via Augmented Prompt Ensembles Mingjian Jiang, Yangjun Ruan, Sicong Huang, Saifei Liao, Silviu Pitis, Roger Baker Grosse, Jimmy Ba

ICML 2023 Efficient Parametric Approximations of Neural Network Function Space Distance Nikita Dhawan, Sicong Huang, Juhan Bae, Roger Baker Grosse

ICLR 2023 Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse

ICMLW 2023 Statistics Estimation in Neural Network Training: A Recursive Identification Approach Ruth Crasto, Xuchan Bao, Roger Baker Grosse

ICLR 2022 Improving Mutual Information Estimation with Annealed and Energy-Based Bounds Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani

ICLR 2021 INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger Baker Grosse

ICLR 2021 When Does Preconditioning Help or Hurt Generalization? Shun-ichi Amari, Jimmy Ba, Roger Baker Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu