Schema Selection and Stochastic Inference in Modular Environments. - Paul Smolensky (AAAI, 1983)

A proposal for user centered system documentation. - Claire O'Malley; Paul Smolensky; Liam Bannon; E. Conway; J. Graham; J. Sokolov; Melissa Lee Monty (CHI, 1983)

The impact and issues of the fifth generation: Ethical issues in new computing technologies. - Rob Kling; Terry Winograd; Paul Smolensky; Roland Schinzinger (ACM Annual Conference, 1984)

Ethical questions and military dominance in next generation computing. - Paul Smolensky (ACM Annual Conference, 1984)

Social science and system design: interdisciplinary collaborations. - Lucy A. Suchman; William O. Beeman; Michael R. Pear; Barbara A. Fox; Paul Smolensky (CHI, 1987)

Constraint-Based Hypertext for Argumentation. - Paul Smolensky; Brigham Bell; Barbara A. Fox; Roger King; Clayton H. Lewis (Hypertext, 1987)

Analysis of Distributed Representation of Constituent Structure in Connectionist Systems. - Paul Smolensky (NIPS, 1987)

Connectionist AI, symbolic AI, and the brain. - Paul Smolensky (Artif. Intell. Rev., 1987)

Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment. - Michael Mozer; Paul Smolensky (NIPS, 1988)

Distributed Recursive Structure Processing. - Geraldine Legendre; Yoshiro Miyata; Paul Smolensky (NIPS, 1990)

Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems. - Paul Smolensky (Artif. Intell., 1990)

Rule Induction through Integrated Symbolic and Subsymbolic Processing. - Clayton McMillan; Michael Mozer; Paul Smolensky (NIPS, 1991)

Harmonic Grammars for Formal Languages. - Paul Smolensky (NIPS, 1992)

Dynamic Conflict Resolution in a Connectionist Rule-Based System. - Clayton McMillan; Michael Mozer; Paul Smolensky (IJCAI, 1993)

Optimality Theory: Universal Grammar, Learning and Parsing Algorithms, and Connectionist Foundations (Abstract). - Paul Smolensky; Bruce Tesar (ACL, 1994)

Grammar-based connectionist approaches to language. - Paul Smolensky (Cogn. Sci., 1999)

Harmony in Linguistic Cognition. - Paul Smolensky (Cogn. Sci., 2006)

Introduction to the 2006 Rumelhart Prize Special Issue Honoring Roger Shepard. - Paul Smolensky (Cogn. Sci., 2008)

The Rumelhart Prize at 10. - William Bechtel; Marlene Behrmann; Nick Chater; Robert J. Glushko; Robert L. Goldstone; Paul Smolensky (Cogn. Sci., 2010)

Subsymbolic Computation Theory for the Human Intuitive Processor. - Paul Smolensky (CiE, 2012)

A Bayesian Model of Biases in Artificial Language Learning: The Case of a Word-Order Universal. - Jennifer Culbertson; Paul Smolensky (Cogn. Sci., 2012)

On the Asymmetrical Difficulty of Acquiring Person Reference in French: Production Versus Comprehension. - Geraldine Legendre; Paul Smolensky (J. Log. Lang. Inf., 2012)

Cognitive Biases, Linguistic Universals, and Constraint-Based Grammar Learning. - Jennifer Culbertson; Paul Smolensky; Colin Wilson (Top. Cogn. Sci., 2013)

Optimization and Quantization in Gradient Symbol Systems: A Framework for Integrating the Continuous and the Discrete in Cognition. - Paul Smolensky; Matthew Goldrick 001; Donald Mathis (Cogn. Sci., 2014)

Bifurcation analysis of a Gradient Symbolic Computation model of incremental processing. - Pyeong Whan Cho; Paul Smolensky (CogSci, 2016)

Reasoning in Vector Space: An Exploratory Study of Question Answering. - Moontae Lee; Xiaodong He 001; Wen-tau Yih; Jianfeng Gao 001; Li Deng 001; Paul Smolensky (ICLR (Poster), 2016)

Basic Reasoning with Tensor Product Representations. - Paul Smolensky; Moontae Lee; Xiaodong He 001; Wen-tau Yih; Jianfeng Gao 001; Li Deng 001 (CoRR, 2016)

Deep Learning of Grammatically-Interpretable Representations Through Question-Answering. - Hamid Palangi; Paul Smolensky; Xiaodong He 001; Li Deng 001 (CoRR, 2017)

Tensor Product Generation Networks. - Qiuyuan Huang; Paul Smolensky; Xiaodong He 001; Li Deng 001; Dapeng Oliver Wu (CoRR, 2017)

A Neural-Symbolic Approach to Natural Language Tasks. - Qiuyuan Huang; Paul Smolensky; Xiaodong He 001; Li Deng 001; Dapeng Oliver Wu (CoRR, 2017)

Question-Answering with Grammatically-Interpretable Representations. - Hamid Palangi; Paul Smolensky; Xiaodong He 001; Li Deng 001 (AAAI, 2018)

Dynamic encoding of structural uncertainty in gradient symbols. - Pyeong Whan Cho; Matthew Goldrick 001; Richard L. Lewis; Paul Smolensky (CMCL, 2018)

Learning and Analyzing Vector Encoding of Symbolic Representation. - Roland Fernandez; Asli Celikyilmaz; Paul Smolensky; Rishabh Singh (ICLR (Workshop), 2018)

Tensor Product Generation Networks for Deep NLP Modeling. - Qiuyuan Huang; Paul Smolensky; Xiaodong He 001; Li Deng 001; Dapeng Oliver Wu (NAACL-HLT, 2018)

Discrete symbolic optimization and Boltzmann sampling by continuous neural dynamics: Gradient Symbolic Computation. - Paul F. Tupper; Paul Smolensky; Pyeong Whan Cho (CoRR, 2018)

Learning and analyzing vector encoding of symbolic representations. - Roland Fernandez; Asli Celikyilmaz; Rishabh Singh; Paul Smolensky (CoRR, 2018)

Predicting Argumenthood of English Preposition Phrases. - Najoung Kim; Kyle Rawlins; Benjamin Van Durme; Paul Smolensky (CoRR, 2018)

Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations. - Shuai Tang; Paul Smolensky; Virginia R. de Sa (CoRR, 2018)

Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations. - Matthias Lalisse; Paul Smolensky (CoRR, 2018)

Predicting the Argumenthood of English Prepositional Phrases. - Najoung Kim; Kyle Rawlins; Benjamin Van Durme; Paul Smolensky (AAAI, 2019)

RNNs implicitly implement tensor-product representations. - R. Thomas McCoy; Tal Linzen; Ewan Dunbar; Paul Smolensky (ICLR (Poster), 2019)

Natural- to formal-language generation using Tensor Product Representations. - Kezhen Chen; Qiuyuan Huang; Hamid Palangi; Paul Smolensky; Kenneth D. Forbus; Jianfeng Gao 001 (CoRR, 2019)

Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving. - Imanol Schlag; Paul Smolensky; Roland Fernandez; Nebojsa Jojic; Jürgen Schmidhuber; Jianfeng Gao 001 (CoRR, 2019)

HUBERT Untangles BERT to Improve Transfer across NLP Tasks. - Mehrad Moradshahi; Hamid Palangi; Monica S. Lam; Paul Smolensky; Jianfeng Gao 001 (CoRR, 2019)

Discovering the Compositional Structure of Vector Representations with Role Learning Networks. - Paul Soulos; R. Thomas McCoy; Tal Linzen; Paul Smolensky (BlackboxNLP@EMNLP, 2020)

Universal linguistic inductive biases via meta-learning. - Richard Thomas McCoy; Erin Grant; Paul Smolensky; Tom Griffiths 001; Tal Linzen (CogSci, 2020)

Invertible Tree Embeddings using a Cryptographic Role Embedding Scheme. - Coleman Haley; Paul Smolensky (COLING, 2020)

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 001 (ICML, 2020)

Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language. - Hassan Akbari; Hamid Palangi; Jianwei Yang; Sudha Rao; Asli Celikyilmaz; Roland Fernandez; Paul Smolensky; Jianfeng Gao 001; Shih-Fu Chang (CoRR, 2020)

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 (CogSci, 2021)

Compositional processing emerges in neural networks solving math problems. - Jacob L. Russin; Roland Fernandez; Hamid Palangi; Eric Rosen; Nebojsa Jojic; Paul Smolensky; Jianfeng Gao 001 (CogSci, 2021)

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 001 (NAACL-HLT, 2021)

Scalable knowledge base completion with superposition memories. - Matthias Lalisse; Eric Rosen; Paul Smolensky (CoRR, 2021)

Distributed neural encoding of binding to thematic roles. - Matthias Lalisse; Paul Smolensky (CoRR, 2021)

Neurocompositional Computing: From the Central Paradox of Cognition to a New Generation of AI Systems. - Paul Smolensky; Richard Thomas McCoy; Roland Fernandez; Matthew Goldrick 001; Jianfeng Gao 001 (AI Mag., 2022)

PIPS: A Parallel Planning Model of Sentence Production. - Laurel Brehm; Pyeong Whan Cho; Paul Smolensky; Matthew A. Goldrick (Cogn. Sci., 2022)

Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages. - Paul Soulos; Sudha Rao; Caitlin Smith; Eric Rosen; Asli Celikyilmaz; R. Thomas McCoy; Yichen Jiang; Coleman Haley; Roland Fernandez; Hamid Palangi; Jianfeng Gao 001; Paul Smolensky (CoRR, 2022)

Uncontrolled Lexical Exposure Leads to Overestimation of Compositional Generalization in Pretrained Models. - Najoung Kim; Tal Linzen; Paul Smolensky (CoRR, 2022)

Differentiable Tree Operations Promote Compositional Generalization. - Paul Soulos; Edward J. Hu; Kate McCurdy; Yunmo Chen; Roland Fernandez; Paul Smolensky; Jianfeng Gao 001 (ICML, 2023)

Implicit Chain of Thought Reasoning via Knowledge Distillation. - Yuntian Deng; Kiran Prasad; Roland Fernandez; Paul Smolensky; Vishrav Chaudhary; Stuart M. Shieber (CoRR, 2023)

How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN. - R. Thomas McCoy; Paul Smolensky; Tal Linzen; Jianfeng Gao 001; Asli Celikyilmaz (Trans. Assoc. Comput. Linguistics, 2023)

Toward Compositional Behavior in Neural Models: A Survey of Current Views. - Kate McCurdy; Paul Soulos; Paul Smolensky; Roland Fernandez; Jianfeng Gao 001 (EMNLP, 2024)

Compositional Generalization Across Distributional Shifts with Sparse Tree Operations. - Paul Soulos; Henry Conklin; Mattia Opper; Paul Smolensky; Jianfeng Gao 001; Roland Fernandez (NeurIPS, 2024)

Mechanisms of Symbol Processing for In-Context Learning in Transformer Networks. - Paul Smolensky; Roland Fernandez; Zhenghao Herbert Zhou; Mattia Opper; Jianfeng Gao 001 (CoRR, 2024)

TRA: Better Length Generalisation with Threshold Relative Attention. - Mattia Opper; Roland Fernandez; Paul Smolensky; Jianfeng Gao 001 (Trans. Mach. Learn. Res., 2025)