The Adaptive Nature of Eye Movements in Linguistic Tasks: How Payoff and Architecture Shape Speed-Accuracy Trade-Offs. - Richard L. Lewis; Michael Shvartsman; Satinder Singh 001 (Top. Cogn. Sci., 2013)

Computationally Rational Saccadic Control: An Explanation of Spillover Effects Based on Sampling from Noisy Perception and Memory. - Michael Shvartsman; Richard L. Lewis; Satinder Singh 001 (CMCL@ACL, 2014)

A Theory of Decision Making Under Dynamic Context. - Michael Shvartsman; Vaibhav Srivastava; Jonathan D. Cohen 003 (NIPS, 2015)

Adaptive response priors in context-dependent decision-making. - Olga Lositsky; Michael Shvartsman; Robert C. Wilson; Jonathan D. Cohen 003 (CogSci, 2017)

Matrix-normal models for fMRI analysis. - Michael Shvartsman; Narayanan Sundaram; Mikio Aoi; Adam Charles; Theodore L. Willke; Jonathan D. Cohen 003 (AISTATS, 2018)

Constraints associated with cognitive control and the stability-flexibility dilemma. - Sebastian Musslick; Seong Jun Jang; Michael Shvartsman; Amitai Shenhav; Jonathan D. Cohen 003 (CogSci, 2018)

Asymmetric Switch Costs as a Function of Task Strength. - Markus Spitzer; Sebastian Musslick; Michael Shvartsman; Amitai Shenhav; Jonathan D. Cohen 003 (CogSci, 2019)

Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis. - Ming Bo Cai; Michael Shvartsman; Anqi Wu; Hejia Zhang; Xia Zhu (CoRR, 2020)

Unifying Few- and Zero-Shot Egocentric Action Recognition. - Tyler R. Scott; Michael Shvartsman; Karl Ridgeway (CoRR, 2020)

Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation. - Benjamin Letham; Phillip Guan; Chase Tymms; Eytan Bakshy; Michael Shvartsman (AISTATS, 2022)

Perceptual Requirements for Eye-Tracked Distortion Correction in VR. - Phillip Guan; Olivier Mercier; Michael Shvartsman; Douglas Lanman (SIGGRAPH (Conference Paper Track), 2022)

A Semi-parametric Model for Decision Making in High-Dimensional Sensory Discrimination Tasks. - Stephen Keeley; Benjamin Letham; Craig Sanders; Chase Tymms; Michael Shvartsman (AAAI, 2023)

Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences. - Michael Shvartsman; Benjamin Letham; Stephen Keeley (CoRR, 2023)

Response Time Improves Gaussian Process Models for Perception and Preferences. - Michael Shvartsman; Benjamin Letham; Eytan Bakshy; Stephen Keeley (UAI, 2024)

The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements. - Bingchen Zhao; Despoina Magka; Minqi Jiang; Xian Li; Roberta Raileanu; Tatiana Shavrina; Jean-Christophe Gagnon-Audet; Kelvin Niu; Shagun Sodhani; Michael Shvartsman; Andrei Lupu; Alisia Maria Lupidi; et al. (CoRR, 2025)

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench. - Edan Toledo; Karen Hambardzumyan; Martin Josifoski; Rishi Hazra; Nicolas Mario Baldwin; Alexis Audran-Reiss; Michael Kuchnik; Despoina Magka; Minqi Jiang; Alisia Maria Lupidi; Andrei Lupu; Roberta Raileanu; et al. (CoRR, 2025)

Scaling and Distilling Transformer Models for sEMG. - Nicholas Mehlman; Jean-Christophe Gagnon-Audet; Michael Shvartsman; Kelvin Niu; Alexander H. Miller; Shagun Sodhani (CoRR, 2025)