Publications

• Human Curriculum Effects Emerge with In-Context Learning in Neural Networks. Russin, J., Pavlick, E., Frank M. J. CogSci 2024 2024
• Multiple Realizability and the Rise of Deep Learning. McGrath, S. W., Russin, J. CogSci 2024 2024
• Is human compositionality meta-learned? Russin, J., McGrath, S. W., Pavlick, E., Frank, M. J. Commentary in Behavioral and Brain Sciences (forthcoming) 2024
• From Frege to ChatGPT: Compositionality in Language, Cognition, and Deep Neural Networks Russin, J.*, McGrath, S. W.∗, Williams, D., Elber-Dorozko, L. Forthcoming * Equal contribution 2024
• The Relational Bottleneck as an Inductive Bias for Efficient Abstraction Webb T. W., Frankland, S. M., Altabaa, A., Krishnamurthy, K., Campbell, D., Russin, J., O’Reilly, R., Lafferty, J., Cohen, J. D. Trends in Cognitive Sciences 2024
• How Can Deep Neural Networks Inform Theory in Psychological Science? McGrath, S. W.*, Russin, J.*, Pavlick, E., Feiman, R. Forthcoming * Equal contribution 2024
• Properties of LoTs: The footprints or the bear itself? McGrath, S. W.*, Russin, J.*, Pavlick, E., Feiman, R. Commentary published in Behavioral and Brain Sciences. 2023
• Compositionality and Cognitive Control in Neural Networks. Russin, J. [Doctoral Dissertation, University of California, Davis]. 2023
• Systematicity Emerges in Transformers when Abstract Grammatical Roles Guide Attention. Chakravarthy, A., Russin, J.*, O’Reilly, R. NAACL SRW 2022. * Equal contribution 2022
• The Geometry of Map-Like Representations under Dynamic Cognitive Control Zolfaghar, M.*, Russin, J.*, Park, S.*, Boorman E., O’Reilly, R. CogSci 2022. * Equal contribution 2022
• A Neural Network Model of Continual Learning with Cognitive Control Russin, J., Zolfaghar, M., Park, S., Boorman, E., O’Reilly, R. CogSci 2022. 2022
• The Structure of Systematicity in the Brain O'Reilly, R. C., Ranganath, C., Russin, J. Current Directions in Psychological Science 2022
• Deep Predictive Learning with Local Gradient Information Russin, J., O'Reilly, R. C. Abstract accepted as a poster presentation at: Bernstein Conference 2021. 2021
• Complementary Structure-Learning Neural Networks for Relational Reasoning Russin, J.*, Zolfaghar, M.*, Park, S., Boorman E., O’Reilly, R. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, CogSci 2021. * Equal contribution 2021
• Compositional Processing Emerges in Neural Networks Solving Math Problems Russin, J., Fernandez, R., Palangi, H., Rosen, E., Jojic, N., Smolensky, P., Gao, J. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, CogSci 2021 2021
• Deep Predictive Learning in Neocortex and Pulvinar O'Reilly, R. C., Russin, J., Zolfaghar, M., Rohrlich, J. Journal of Cognitive Neuroscience 2021
• Deep Learning Needs a Prefrontal Cortex Russin, J., O’Reilly, R. C., Bengio, Y. Bridging AI and Cognitive Science, ICLR 2020 Workshop 2020
• Systematicity in a Recurrent Neural Network by Factorizing Syntax and Semantics Russin, J., Jo, J., O’Reilly, R. C., Bengio, Y. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society, CogSci 2020 2020
• Compositional Generalization by Factorizing Alignment and Translation Russin, J., Jo, J., O’Reilly, R. C., Bengio, Y. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop 2020
• How Sequential Interactive Processing Within Frontostriatal Loops Supports a Continuum of Habitual to Controlled Processing O’Reilly, R. C., Nair, A., Russin, J., & Herd, S. A. Frontiers in Psychology 2020
• Effects of the Presence and Absence of Amino Acids on Translation, Signaling and Long‐Term Depression in Hippocampal Slices from Fmr1 Knockout Mice Cooke, S. K., Russin, J., Moulton, K., Nadel, J., Loutaev, I., Gu, Q., Li, Z. and Smith, C. B. Journal of Neurochemistry 2019
• Computational Models of Motivated Frontal Function O’Reilly, R.C., Russin, J., & Herd, S.A. In: D’Esposito M and Grafman JH, (eds). The Frontal Lobes. San Diego: Elsevier BV, 2019: 317-332 2019