Szymanik, J. (2007) Strong Meaning Hypothesis from a Computational Perspective.

In F. Roelofsen M. Aloni, P. Dekker (Eds.), Proceedings of the Sixteenth Amsterdam Colloquium (pp 211-216)

Szymanik, J. (2007) A Note on some Neuroimaging Study of Natural Language Quantifiers Comprehension.

Neuropsychologia, Vol. 45 (pp 2158-2160)

Article | https://doi.org/10.1016/j.neuropsychologia.2007.01.016 | UvA-DARE

Szymanik, J. (2007) Computational semantics for monadic quantifiers in natural language.

Studia Semiotyczne, Vol. 26 (pp 219-244)

Article | UvA-DARE

Szymanik, J. (2009) The computational complexity of quantified reciprocals.

In Bosch, P. Gabelaia, D. Lang, J. (Eds.), Logic, Language, and Computation: 7th International Tbilisi Symposium on Logic, Language, and Computation, TbiLLC 2007, Tbilisi, Georgia, October 1-5, 2007 : revised selected papers (pp 139-152) (Lecture Notes in Computer Science
Lecture Notes in Artificial Intelligence
FoLLI Publications on Logic, Language and Information, Vol. 5422). Springer.

Szymanik, J. (2009) Almost all complex quantifiers are simple.

Paper | http://www.jakubszymanik.com/papers/complex_qua.pdf | UvA-DARE

Szymanik, J. (2009) Quantifiers in TIME and SPACE : computational complexity of generalized quantifiers in natural language.

Institute for Logic, Language and Computation.

Thesis, fully internal | UvA-DARE

Szymanik, J. (2010) Computational complexity of polyadic lifts of generalized quantifiers in natural language.

Linguistics and Philosophy, Vol. 33 (pp 215-250)

Article | https://doi.org/10.1007/s10988-010-9076-z | UvA-DARE

Szymanik, J. (2010) Almost all complex quantifiers are simple.

In Ebert, C. Jäger, G. Michaelis, J. (Eds.), The Mathematics of Language: 10th and 11th Biennial Conference MOL 10, Los Angeles, CA, USA, July 28-30, 2007 and MOL 11, Bielefeld, Germany, August 20-21, 2009 : revised selected papers (pp 272-280) (Lecture Notes in Computer Science
Lecture Notes in Artificial Intelligence
FoLLI Publications on Logic, Language and Information, Vol. 6149). Springer.

Szymanik, J. (2013) Backward Induction is PTIME-complete.

In Grossi, D. Roy, O. Huang, H. (Eds.), Logic, Rationality, and Interaction: 4th International Workshop, LORI 2013, Hangzhou, China, October 9-12, 2013 : proceedings (pp 352-356) (Lecture Notes in Computer Science
FoLLI Publications on Logic, Language and Information, Vol. 8196). Springer.

Szymanik, J. (2013) Communication and cooperation.

In van Benthem, J. Liu, F. (Eds.), Logic Across the University: Foundations and Applications: proceedings of the Tsinghua Logic Conference, Beijing, 2013 (pp 372-375) (Studies in Logic, Vol. 47). College Publications.

Szymanik, J. (2016) Quantifiers and Cognition: Logical and Computational Perspectives.

Studies in Linguistics and Philosophy, Vol. 96. Springer.

Book | https://doi.org/10.1007/978-3-319-28749-2 | UvA-DARE

Szymanik, J. (2019) Bridging Logic, Philosophy, Computer and Cognitive Science: in the Memory of Marcin Mostowski (1955-2017): Introduction.

Fundamenta Informaticae, Vol. 164 (pp i-ii)

Article | https://doi.org/10.3233/FI-2019-1769 | UvA-DARE

Tagliola, C., Adriaans, P., van Aartrijk, M.L. (2002) Al on the ocean: The Robosail project.

In van Harmelen, F. (Eds.), Ecai 2002 (pp 653-657). IOS Press.

Takmaz, E., Brandizzi, N., Giulianelli, M., Pezzelle, S., Fernández, R. (2023) Speaking the Language of Your Listener: Audience-Aware Adaptation via Plug-and-Play Theory of Mind.

In Rogers, A. Boyd-Graber, J. Okazaki, N. (Eds.), Findings of the Association for Computational Linguistics: ACL 2023: July 9-14, 2023 (pp 4198-4217). Association for Computational Linguistics.

Takmaz, E., Giulianelli, M., Pezzelle, S., Sinclair, A., Fernández, R. (2020) Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts.

In Webber, B. Cohn, T. He, Y. Liu, Y. (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp 4350-4368). The Association for Computational Linguistics.

Takmaz, E., Pezzelle, S., Beinborn, L.M., Fernández, R. (2020) Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gaze.

In Webber, B. Cohn, T. He, Y. Liu, Y. (Eds.), 2020 Conference on Empirical Methods in Natural Language Processing: EMNLP 2020 : proceedings of the conference : November 16-20, 2020 (pp 4664–4677). The Association for Computational Linguistics.

Takmaz, E., Pezzelle, S., Fernández, R. (2022) Time Alignment between Gaze and Speech in Image Descriptions: Exploring Theories of Linearization.

Abstract | https://escholarship.org/uc/item/83w56904 | UvA-DARE

Takmaz, E., Pezzelle, S., Fernández, R. (2022) Less Descriptive yet Discriminative: Quantifying the Properties of Multimodal Referring Utterances via CLIP.

In Chersoni, E. Hollenstein, N. Jacobs, C. Oseki, Y. Prévot, L. Santus, E. (Eds.), Workshop on Cognitive Modeling and Computational Linguistics: CMCL 2022 : proceedings of the workshop : May 26, 2022 (pp 36-42). Association for Computational Linguistics.

Takmaz, E. (2022) Team DMG at CMCL 2022 Shared Task: Transformer Adapters for the Multi- and Cross-Lingual Prediction of Human Reading Behavior.

In Chersoni, E. Hollenstein, N. Jacobs, C. Oseki, Y. Prévot, L. Santus, E. (Eds.), Workshop on Cognitive Modeling and Computational Linguistics: CMCL 2022 : proceedings of the workshop : May 26, 2022 (pp 136-144). Association for Computational Linguistics.

Takmaz, E. (2024) Visual and linguistic processes in deep neural networks: A cognitive perspective.

ILLC Dissertation series

Thesis, fully internal | UvA-DARE