Smolensky, Paul

Tensor product variable binding and the representation of symbolic structures in connectionist systems

Smolensky, P. (1990) · Artificial Intelligence

Neural Networks and ApplicationsCognitive Computing and Networks

Cited by 959

How much do language models copy from their training data? evaluating linguistic novelty in text generation using RAVEN

McCoy, R. T., Smolensky, P., Linzen, T., Gao, J., & Celikyilmaz, A. (2023) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 70

How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN

McCoy, R. T., Smolensky, P., Linzen, T., Gao, J., & Celikyilmaz, A. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 70

Universal linguistic inductive biases via meta-learning

McCoy, R. T., Grant, E., Smolensky, P., Griffiths, T. L., & Linzen, T. (2020) · arXiv

Language Development and DisordersDomain Adaptation and Few-Shot Learning

Cited by 13

Implicit Chain of Thought Reasoning via Knowledge Distillation

Deng, Y., Prasad, K., Fernandez, R., Smolensky, P., Chaudhary, V., & Shieber, S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1