| 2024 | CogSci | Structural Generalization of Modification in Adult Learners of an Artificial Language. | Najoung Kim, Paul Smolensky |
| 2024 | EMNLP | Toward Compositional Behavior in Neural Models: A Survey of Current Views. | Kate McCurdy, Paul Soulos, Paul Smolensky, Roland Fernandez, Jianfeng Gao |
| 2023 | ICML | Differentiable Tree Operations Promote Compositional Generalization. | Paul Soulos, Edward J. Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao |
| 2021 | CogSci | Infinite use of finite means? Evaluating the generalization of center embedding learned from an artificial grammar. | Richard Thomas McCoy, Jennifer Culbertson, Paul Smolensky, Geraldine Legendre |
| 2021 | CogSci | Compositional processing emerges in neural networks solving math problems. | Jacob L. Russin, Roland Fernandez, Hamid Palangi, Eric Rosen, Nebojsa Jojic, Paul Smolensky, Jianfeng Gao |
| 2021 | NAACL | Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization. | Yichen Jiang, Asli Celikyilmaz, Paul Smolensky, Paul Soulos, Sudha Rao, Hamid Palangi, Roland Fernandez, Caitlin Smith, Mohit Bansal, Jianfeng Gao |
| 2020 | CogSci | Universal linguistic inductive biases via meta-learning. | Richard Thomas McCoy, Erin Grant, Paul Smolensky, Tom Griffiths, Tal Linzen |
| 2020 | COLING | Invertible Tree Embeddings using a Cryptographic Role Embedding Scheme. | Coleman Haley, Paul Smolensky |
| 2020 | ICML | Mapping natural-language problems to formal-language solutions using structured neural representations. | Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Kenneth D. Forbus, Jianfeng Gao |
| 2019 | AAAI | Predicting the Argumenthood of English Prepositional Phrases. | Najoung Kim, Kyle Rawlins, Benjamin Van Durme, Paul Smolensky |
| 2019 | ICLR | RNNs implicitly implement tensor-product representations. | R. Thomas McCoy, Tal Linzen, Ewan Dunbar, Paul Smolensky |
| 2018 | AAAI | Question-Answering with Grammatically-Interpretable Representations. | Hamid Palangi, Paul Smolensky, Xiaodong He, Li Deng |
| 2018 | ICLR | Learning and Analyzing Vector Encoding of Symbolic Representation. | Roland Fernandez, Asli Celikyilmaz, Paul Smolensky, Rishabh Singh |
| 2018 | NAACL | Tensor Product Generation Networks for Deep NLP Modeling. | Qiuyuan Huang, Paul Smolensky, Xiaodong He, Li Deng, Dapeng Oliver Wu |
| 2016 | CogSci | Bifurcation analysis of a Gradient Symbolic Computation model of incremental processing. | Pyeong Whan Cho, Paul Smolensky |
| 2012 | CiE | Subsymbolic Computation Theory for the Human Intuitive Processor. | Paul Smolensky |
| 1994 | ACL | Optimality Theory: Universal Grammar, Learning and Parsing Algorithms, and Connectionist Foundations (Abstract). | Paul Smolensky, Bruce Tesar |
| 1993 | IJCAI | Dynamic Conflict Resolution in a Connectionist Rule-Based System. | Clayton McMillan, Michael Mozer, Paul Smolensky |
| 1987 | CHI | Social science and system design: interdisciplinary collaborations. | Lucy A. Suchman, William O. Beeman, Michael R. Pear, Barbara A. Fox, Paul Smolensky |
| 1983 | AAAI | Schema Selection and Stochastic Inference in Modular Environments. | Paul Smolensky |
| 1983 | CHI | A proposal for user centered system documentation. | Claire O'Malley, Paul Smolensky, Liam Bannon, E. Conway, J. Graham, J. Sokolov, Melissa Lee Monty |