Should I use TensorFlow. - Martin Schrimpf (CoRR, 2016)

On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations. - Nicholas Cheney; Martin Schrimpf; Gabriel Kreiman (CoRR, 2017)

Recurrent computations for visual pattern completion. - Hanlin Tang; Bill Lotter; Martin Schrimpf; Ana Paredes; Josue Ortega Caro; Walter Hardesty; David D. Cox; Gabriel Kreiman (CoRR, 2017)

A Flexible Approach to Automated RNN Architecture Generation. - Martin Schrimpf; Stephen Merity; James Bradbury 002; Richard Socher (ICLR (Workshop), 2018)

Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. - Jonas Kubilius; Martin Schrimpf; Ha Hong; Najib J. Majaj; Rishi Rajalingham; Elias B. Issa; Kohitij Kar; Pouya Bashivan; Jonathan Prescott-Roy; Kailyn Schmidt; Aran Nayebi; Daniel Bear; et al. (NeurIPS, 2019)

Continual Learning with Self-Organizing Maps. - Pouya Bashivan; Martin Schrimpf; Robert Ajemian; Irina Rish; Matthew Riemer; Yuhai Tu (CoRR, 2019)

Removable and/or Repeated Units Emerge in Overparametrized Deep Neural Networks. - Stephen Casper; Xavier Boix; Vanessa D'Amario; Ling Guo; Martin Schrimpf; Kasper Vinken; Gabriel Kreiman (CoRR, 2019)

Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations. - Joel Dapello; Tiago Marques; Martin Schrimpf; Franziska Geiger; David D. Cox; James J. DiCarlo (NeurIPS, 2020)

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. - Chuang Gan 001; Jeremy Schwartz; Seth Alter; Martin Schrimpf; James Traer; Julian De Freitas; Jonas Kubilius; Abhishek Bhandwaldar; Nick Haber; Megumi Sano; Kuno Kim; Elias Wang; et al. (CoRR, 2020)

Frivolous Units: Wider Networks Are Not Really That Wide. - Stephen Casper; Xavier Boix; Vanessa D'Amario; Ling Guo; Martin Schrimpf; Kasper Vinken; Gabriel Kreiman (AAAI, 2021)

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation. - Chuang Gan 001; Jeremy Schwartz; Seth Alter; Damian Mrowca; Martin Schrimpf; James Traer; Julian De Freitas; Jonas Kubilius; Abhishek Bhandwaldar; Nick Haber; Megumi Sano; Kuno Kim; et al. (NeurIPS Datasets and Benchmarks, 2021)

Unsupervised neural network models of the ventral visual stream. - Chengxu Zhuang; Siming Yan; Aran Nayebi; Martin Schrimpf; Michael C. Frank; James J. DiCarlo; Daniel L. K. Yamins (Proc. Natl. Acad. Sci. USA, 2021)

Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream. - Franziska Geiger; Martin Schrimpf; Tiago Marques; James J. DiCarlo (ICLR, 2022)

Modeling Visual Impairments with Artificial Neural Networks: a Review. - Lucia Schiatti; Monica Gori; Martin Schrimpf; Giulia Cappagli; Federica Morelli; Sabrina Signorini; Boris Katz; Andrei Barbu (ICCV (Workshops), 2023)

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness. - Joel Dapello; Kohitij Kar; Martin Schrimpf; Robert Baldwin Geary; Michael Ferguson; David Daniel Cox; James J. DiCarlo (ICLR, 2023)

Instruction-tuning Aligns LLMs to the Human Brain. - Khai Loong Aw; Syrielle Montariol; Badr AlKhamissi; Martin Schrimpf; Antoine Bosselut (CoRR, 2023)

Brain-Like Language Processing via a Shallow Untrained Multihead Attention Network. - Badr AlKhamissi; Greta Tuckute; Antoine Bosselut; Martin Schrimpf (CoRR, 2024)

Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data. - Badr AlKhamissi; Yingtian Tang; Abdülkadir Gökce; Johannes Mehrer; Martin Schrimpf (CoRR, 2024)

Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream. - Abdülkadir Gökce; Martin Schrimpf (CoRR, 2024)

TopoLM: brain-like spatio-functional organization in a topographic language model. - Neil Rathi; Johannes Mehrer; Badr AlKhamissi; Taha Osama A Binhuraib; Nicholas M. Blauch; Martin Schrimpf (ICLR, 2025)

The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units. - Badr AlKhamissi; Greta Tuckute; Antoine Bosselut; Martin Schrimpf (NAACL (Long Papers), 2025)

From Language to Cognition: How LLMs Outgrow the Human Language Network. - Badr AlKhamissi; Greta Tuckute; Yingtian Tang; Taha Binhuraib; Antoine Bosselut; Martin Schrimpf (CoRR, 2025)

Contour Integration Underlies Human-Like Vision. - Ben Lonnqvist; Elsa Scialom; Abdülkadir Gökce; Zehra Merchant; Michael H. Herzog; Martin Schrimpf (CoRR, 2025)

Mixture of Cognitive Reasoners: Modular Reasoning with Brain-Like Specialization. - Badr AlKhamissi; C. Nicolò De Sabbata; Zeming Chen 001; Martin Schrimpf; Antoine Bosselut (CoRR, 2025)