Research
My work intersects Cognitive Science, Computational Linguistics, Machine Learning, and Neuroscience.
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Differentiable Tree Operations Promote Compositional Generalization
Paul Soulos, Edward Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao
Proceedings of the 40th International Conference on Machine Learning, 2023
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Disentangled Face Representations in Humans and Machines
Paul Soulos, Leyla Isik
Conference on Cognitive Computational Neuroscience, 2022
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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, Paul Smolensky
Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021), 2021
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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
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
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Discovering the Compositional Structure of Vector Representations with Role Learning Networks
Paul Soulos, R. Thomas McCoy, Tal Linzen, Paul Smolensky
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020
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Learning to generalize like humans using basic-level object labels
Joshua C Peterson, Paul Soulos, Aida Nematzadeh, Thomas L Griffiths
Journal of Vision, 2019
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