Paul Smolensky

Publication Activity (10 Years)

Years Active: 1983-2023
Publications (10 Years): 45

Top Topics

Natural Language

Top Venues

Publications

Paul Soulos, Edward J. Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao
Differentiable Tree Operations Promote Compositional Generalization. ICML (2023)
Yuntian Deng, Kiran Prasad, Roland Fernandez, Paul Smolensky, Vishrav Chaudhary, Stuart M. Shieber
Implicit Chain of Thought Reasoning via Knowledge Distillation. CoRR (2023)
Paul Soulos, Edward J. Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao
Differentiable Tree Operations Promote Compositional Generalization. CoRR (2023)
R. Thomas McCoy, Paul Smolensky, Tal Linzen, Jianfeng Gao, Asli Celikyilmaz
How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN. Trans. Assoc. Comput. Linguistics 11 (2023)
Laurel Brehm, Pyeong Whan Cho, Paul Smolensky, Matthew A. Goldrick
PIPS: A Parallel Planning Model of Sentence Production. Cogn. Sci. 46 (2) (2022)
Paul Smolensky, R. Thomas McCoy, Roland Fernandez, Matthew Goldrick, Jianfeng Gao
Neurocompositional computing: From the Central Paradox of Cognition to a new generation of AI systems. CoRR (2022)
Paul Smolensky, Richard Thomas McCoy, Roland Fernandez, Matthew Goldrick, Jianfeng Gao
Neurocompositional Computing: From the Central Paradox of Cognition to a New Generation of AI Systems. AI Mag. 43 (3) (2022)
Najoung Kim, Tal Linzen, Paul Smolensky
Uncontrolled Lexical Exposure Leads to Overestimation of Compositional Generalization in Pretrained Models. CoRR (2022)
Paul Soulos, Sudha Rao, Caitlin Smith, Eric Rosen, Asli Celikyilmaz, R. Thomas McCoy, Yichen Jiang, Coleman Haley, Roland Fernandez, Hamid Palangi, Jianfeng Gao, Paul Smolensky
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages. CoRR (2022)
Yichen Jiang, Asli Celikyilmaz, Paul Smolensky, Paul Soulos, Sudha Rao, Hamid Palangi, Roland Fernandez, Caitlin Smith, Mohit Bansal, Jianfeng Gao
Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization. NAACL-HLT (2021)
Richard Thomas McCoy, Jennifer Culbertson, Paul Smolensky, Geraldine Legendre
Infinite use of finite means? Evaluating the generalization of center embedding learned from an artificial grammar. CogSci (2021)
R. Thomas McCoy, Paul Smolensky, Tal Linzen, Jianfeng Gao, Asli Celikyilmaz
How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN. CoRR (2021)
Jacob L. Russin, Roland Fernandez, Hamid Palangi, Eric Rosen, Nebojsa Jojic, Paul Smolensky, Jianfeng Gao
Compositional processing emerges in neural networks solving math problems. CogSci (2021)
Matthias Lalisse, Eric Rosen, Paul Smolensky
Scalable knowledge base completion with superposition memories. CoRR (2021)
Jacob Russin, Roland Fernandez, Hamid Palangi, Eric Rosen, Nebojsa Jojic, Paul Smolensky, Jianfeng Gao
Compositional Processing Emerges in Neural Networks Solving Math Problems. CoRR (2021)
Matthias Lalisse, Paul Smolensky
Distributed neural encoding of binding to thematic roles. CoRR (2021)
Yichen Jiang, Asli Celikyilmaz, Paul Smolensky, Paul Soulos, Sudha Rao, Hamid Palangi, Roland Fernandez, Caitlin Smith, Mohit Bansal, Jianfeng Gao
Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization. CoRR (2021)
Paul Soulos, R. Thomas McCoy, Tal Linzen, Paul Smolensky
Discovering the Compositional Structure of Vector Representations with Role Learning Networks. BlackboxNLP@EMNLP (2020)
Richard Thomas McCoy, Erin Grant, Paul Smolensky, Tom Griffiths, Tal Linzen
Universal linguistic inductive biases via meta-learning. CogSci (2020)
Coleman Haley, Paul Smolensky
Invertible Tree Embeddings using a Cryptographic Role Embedding Scheme. COLING (2020)
R. Thomas McCoy, Erin Grant, Paul Smolensky, Thomas L. Griffiths, Tal Linzen
Universal linguistic inductive biases via meta-learning. CoRR (2020)
Hassan Akbari, Hamid Palangi, Jianwei Yang, Sudha Rao, Asli Celikyilmaz, Roland Fernandez, Paul Smolensky, Jianfeng Gao, Shih-Fu Chang
Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language. CoRR (2020)
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Kenneth D. Forbus, Jianfeng Gao
Mapping natural-language problems to formal-language solutions using structured neural representations. ICML (2020)
Najoung Kim, Kyle Rawlins, Benjamin Van Durme, Paul Smolensky
Predicting the Argumenthood of English Prepositional Phrases. AAAI (2019)
Paul Soulos, Tom McCoy, Tal Linzen, Paul Smolensky
Discovering the Compositional Structure of Vector Representations with Role Learning Networks. CoRR (2019)
Imanol Schlag, Paul Smolensky, Roland Fernandez, Nebojsa Jojic, Jürgen Schmidhuber, Jianfeng Gao
Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving. CoRR (2019)
R. Thomas McCoy, Tal Linzen, Ewan Dunbar, Paul Smolensky
RNNs implicitly implement tensor-product representations. ICLR (Poster) (2019)
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Kenneth D. Forbus, Jianfeng Gao
Natural- to formal-language generation using Tensor Product Representations. CoRR (2019)
Mehrad Moradshahi, Hamid Palangi, Monica S. Lam, Paul Smolensky, Jianfeng Gao
HUBERT Untangles BERT to Improve Transfer across NLP Tasks. CoRR (2019)
R. Thomas McCoy, Tal Linzen, Ewan Dunbar, Paul Smolensky
RNNs Implicitly Implement Tensor Product Representations. CoRR (2018)
Qiuyuan Huang, Paul Smolensky, Xiaodong He, Li Deng, Dapeng Oliver Wu
Tensor Product Generation Networks for Deep NLP Modeling. NAACL-HLT (2018)
Matthias Lalisse, Paul Smolensky
Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations. CoRR (2018)
Shuai Tang, Paul Smolensky, Virginia R. de Sa
Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations. CoRR (2018)
Hamid Palangi, Paul Smolensky, Xiaodong He, Li Deng
Question-Answering with Grammatically-Interpretable Representations. AAAI (2018)
Paul F. Tupper, Paul Smolensky, Pyeong Whan Cho
Discrete symbolic optimization and Boltzmann sampling by continuous neural dynamics: Gradient Symbolic Computation. CoRR (2018)
Najoung Kim, Kyle Rawlins, Benjamin Van Durme, Paul Smolensky
Predicting Argumenthood of English Preposition Phrases. CoRR (2018)
Roland Fernandez, Asli Celikyilmaz, Rishabh Singh, Paul Smolensky
Learning and analyzing vector encoding of symbolic representations. CoRR (2018)
Roland Fernandez, Asli Celikyilmaz, Paul Smolensky, Rishabh Singh
Learning and Analyzing Vector Encoding of Symbolic Representation. ICLR (Workshop) (2018)
Pyeong Whan Cho, Matthew Goldrick, Richard L. Lewis, Paul Smolensky
Dynamic encoding of structural uncertainty in gradient symbols. CMCL (2018)
Hamid Palangi, Paul Smolensky, Xiaodong He, Li Deng
Deep Learning of Grammatically-Interpretable Representations Through Question-Answering. CoRR (2017)
Qiuyuan Huang, Paul Smolensky, Xiaodong He, Li Deng, Dapeng Oliver Wu
A Neural-Symbolic Approach to Natural Language Tasks. CoRR (2017)
Qiuyuan Huang, Paul Smolensky, Xiaodong He, Li Deng, Dapeng Oliver Wu
Tensor Product Generation Networks. CoRR (2017)
Moontae Lee, Xiaodong He, Wen-tau Yih, Jianfeng Gao, Li Deng, Paul Smolensky
Reasoning in Vector Space: An Exploratory Study of Question Answering. ICLR (Poster) (2016)
Paul Smolensky, Moontae Lee, Xiaodong He, Wen-tau Yih, Jianfeng Gao, Li Deng
Basic Reasoning with Tensor Product Representations. CoRR (2016)
Pyeong Whan Cho, Paul Smolensky
Bifurcation analysis of a Gradient Symbolic Computation model of incremental processing. CogSci (2016)
Paul Smolensky, Matthew Goldrick, Donald Mathis
Optimization and Quantization in Gradient Symbol Systems: A Framework for Integrating the Continuous and the Discrete in Cognition. Cogn. Sci. 38 (6) (2014)
Jennifer Culbertson, Paul Smolensky, Colin Wilson
Cognitive Biases, Linguistic Universals, and Constraint-Based Grammar Learning. Top. Cogn. Sci. 5 (3) (2013)
Paul Smolensky
Subsymbolic Computation Theory for the Human Intuitive Processor. CiE (2012)
Geraldine Legendre, Paul Smolensky
On the Asymmetrical Difficulty of Acquiring Person Reference in French: Production Versus Comprehension. J. Log. Lang. Inf. 21 (1) (2012)
Jennifer Culbertson, Paul Smolensky
A Bayesian Model of Biases in Artificial Language Learning: The Case of a Word-Order Universal. Cogn. Sci. 36 (8) (2012)
William Bechtel, Marlene Behrmann, Nick Chater, Robert J. Glushko, Robert L. Goldstone, Paul Smolensky
The Rumelhart Prize at 10. Cogn. Sci. 34 (5) (2010)
Paul Smolensky
Introduction to the 2006 Rumelhart Prize Special Issue Honoring Roger Shepard. Cogn. Sci. 32 (1) (2008)
Paul Smolensky
Harmony in Linguistic Cognition. Cogn. Sci. 30 (5) (2006)
Paul Smolensky
Grammar-based connectionist approaches to language. Cogn. Sci. 23 (4) (1999)
Paul Smolensky, Bruce Tesar
Optimality Theory: Universal Grammar, Learning and Parsing Algorithms, and Connectionist Foundations (Abstract). ACL (1994)
Clayton McMillan, Michael Mozer, Paul Smolensky
Dynamic Conflict Resolution in a Connectionist Rule-Based System. IJCAI (1993)
Paul Smolensky
Harmonic Grammars for Formal Languages. NIPS (1992)
Clayton McMillan, Michael Mozer, Paul Smolensky
Rule Induction through Integrated Symbolic and Subsymbolic Processing. NIPS (1991)
Geraldine Legendre, Yoshiro Miyata, Paul Smolensky
Distributed Recursive Structure Processing. SCAI (1991)
Geraldine Legendre, Yoshiro Miyata, Paul Smolensky
Distributed Recursive Structure Processing. NIPS (1990)
Paul Smolensky
Tensor Product Variable Binding and the Representation of Symbolic Structures in Connectionist Systems. Artif. Intell. 46 (1-2) (1990)
Michael Mozer, Paul Smolensky
Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment. NIPS (1988)
Paul Smolensky
Connectionist AI, symbolic AI, and the brain. Artif. Intell. Rev. 1 (2) (1987)
Paul Smolensky
Analysis of Distributed Representation of Constituent Structure in Connectionist Systems. NIPS (1987)
Lucy A. Suchman, William O. Beeman, Michael R. Pear, Barbara Fox, Paul Smolensky
Social science and system design: interdisciplinary collaborations. CHI (1987)
Paul Smolensky, Brigham Bell, Barbara Fox, Roger King, Clayton H. Lewis
Constraint-Based Hypertext for Argumentation. Hypertext (1987)
Paul Smolensky
Ethical questions and military dominance in next generation computing. ACM Annual Conference (1984)
Rob Kling, Terry Winograd, Paul Smolensky, Roland Schinzinger
The impact and issues of the fifth generation: Ethical issues in new computing technologies. ACM Annual Conference (1984)
Claire O'Malley, Paul Smolensky, Liam Bannon, E. Conway, J. Graham, J. Sokolov, Melissa Lee Monty
A proposal for user centered system documentation. CHI (1983)
Paul Smolensky
Schema Selection and Stochastic Inference in Modular Environments. AAAI (1983)