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  1. Role of Context in Unsupervised Sentence Representation Learning: the…

    Hronský, R., & Keuleers, E. (2023). Role of Context in Unsupervised Sentence Representation Learning: the Case of Dialog Act Modeling.. 8784-8792. Paper presented at The 2023 Conference on Empirical Methods in Natural Language Processing, Singapore, Singapore.
  2. Why transactions matter in thinking about the language environment

    Keuleers, E. (2023). Why transactions matter in thinking about the language environment. https://pif2023.ugent.be/programme/PiF2023Booklet0526.pdf
  3. A binary-tree approach to generating imaginary Chinese characters

    Wang, Y., Hronský, R., & Keuleers, E. (2023). A binary-tree approach to generating imaginary Chinese characters. 120-121. Abstract from Words in the world . https://wordsintheworld.ca/wow-conference/conference-schedule-wow2023/
  4. Does the Choice of a Segmentation Algorithm Affect the Performance of…

    Keuleers, E., & Hronský, R. (2022). Does the Choice of a Segmentation Algorithm Affect the Performance of Text Classifiers? In Proceeding of BNAIC/BeNeLearn 2022 Article 5663 https://bnaic2022.uantwerpen.be/wp-content/uploads/BNAICBeNeLearn_2022_submission_5663.pdf
  5. Word Probability Re-Estimation Using Topic Modeling and Lexical Decis…

    Hronský, R., & Keuleers, E. (2021). Word Probability Re-Estimation Using Topic Modeling and Lexical Decision Data. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 43, pp. 188-194) https://escholarship.org/uc/item/2mm461qs

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