In the 2023 Spring Semester we organized a reading group at the ILLC, bringing together formal semanticists and computational linguists working at our institute to discuss the use of Artificial Neural Networks in modelling human language learning and processing. Below is an archive of the papers we read.
Feel free to keep suggesting papers in our sheet!
April 3rd, 2023
Li, J., Yu, L., & Ettinger, A. (2022). Counterfactual reasoning: Do language models need world knowledge for causal inference? In NeurIPS 2022 Workshop on Neuro Causal and Symbolic AI (nCSI). https://arxiv.org/pdf/2212.03278.pdf
presented by: Tom
time: 11-12am CET
location: LAB42, L6.51
March 27th, 2023
Piantadosi, S. (2023). Modern language models refute Chomsky’s approach to language. LingBuzz. https://lingbuzz.net/lingbuzz/007180
time: 4-5pm CET
location: LAB42, L6.27
March 20th, 2023
Manning, C. D., Clark, K., Hewitt, J., Khandelwal, U., & Levy, O. (2020). Emergent linguistic structure in artificial neural networks trained by self-supervision. Proceedings of the National Academy of Sciences, 117(48), 30046-30054. https://doi.org/10.1073/pnas.1907367117
presented by: Samuel
time: 2-3pm CET
location: LAB42, L6.51
March 13th, 2023
Merrill, W., Warstadt, A., & Linzen, T. (2022). Entailment Semantics Can Be Extracted from an Ideal Language Model. In Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL), pages 176–193, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics. https://aclanthology.org/2022.conll-1.13/
presented by: Taka
time: 4-5pm CET
location: LAB42, L6.51
March 6th, 2023
McClelland, J. L., Hill, F., Rudolph, M., Baldridge, J., & Schütze, H. (2020). Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models. Proceedings of the National Academy of Sciences, 117(42), 25966-25974. https://doi.org/10.1073/pnas.1910416117
presented by: Marianne
time: 4-5pm CET
location: LAB42, L6.51
February 27th, 2023
Jain, S., Vo, V. A., Wehbe, L., & Huth, A. G. (2023). Computational language modeling and the promise of in silico experimentation. Neurobiology of Language, 1-65. https://doi.org/10.1162/nol_a_00101
presented by: Tamar
time: 4-5pm CET
location: LAB42, L6.51
February 21st, 2023
Andrew K Lampinen, Ishita Dasgupta, Stephanie CY Chan, Kory Matthewson, Michael Henry Tessler, Antonia Creswell, James L McClelland, Jane X Wang, and Felix Hill. Can language models learn from explanations in context? arXiv preprint arXiv:2204.02329, 2022. https://arxiv.org/abs/2204.02329
presented by: Taka
time: 4-5pm CET
location: LAB42, L3.06
February 13th, 2023
Lakretz, Y., Desbordes, T., Hupkes, D., & Dehaene, S. (2022, October). Can Transformers Process Recursive Nested Constructions, Like Humans?. In Proceedings of the 29th International Conference on Computational Linguistics (pp. 3226-3232). https://aclanthology.org/2022.coling-1.285/
presented by: Tom
time: 4-5pm CET
location: LAB42, L6.51
February 6th, 2023
Mahowald, K., Ivanova, A. A., Blank, I. A., Kanwisher, N., Tenenbaum, J. B., & Fedorenko, E. (2023). Dissociating language and thought in large language models: a cognitive perspective. arXiv preprint arXiv:2301.06627. https://arxiv.org/abs/2301.06627
presented by: Marianne
time: 4-5pm CET
location: LAB42, L6.51
January 30th, 2023
Warstadt, A., & Bowman, S. R. (2022). What artificial neural networks can tell us about human language acquisition. In Algebraic Structures in Natural Language (pp. 17-60). CRC Press. https://arxiv.org/abs/2208.07998
presented by: Tamar
time: 4-5pm CET
location: LAB42, L6.51