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Cognition, Vol. 120 (pp 380-390)

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Hu, Z., Havrylov, S., Titov, I., Cohen, S.B. (2020) Obfuscation for privacy-preserving syntactic parsing.

In Bouma, G. Matsumoto, Y. Oepen, S. Sagae, K. Seddah, D. Sun, W. Søgaard, A. Tsarfaty, R. Zeman, D. (Eds.), The 16th International Conference on Parsing Technologies and IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies: IWPT 2020 : Proceedings of the Conference : July 9, 2020 (pp 62-72). Association for Computational Linguistics.

Huang, J., Chang, Y., Cheng, X., Kamps, J., Murdock, V., Wen, J.-R., Liu, Y. (2020) SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China.

Association for Computing Machinery.

Book (Editorship) | https://doi.org/10.1145/3397271 | UvA-DARE

Huang, N.T., Deshpande, Y.R., Liu, Y., Alberts, H., Cho, K., Vania, C., Calixto, I. (2020) Learning Robust Multimodal Knowledge Graph Representations.

Paper | https://nhuang37.github.io/publication/multimodalkb/ | UvA-DARE

Huang, R., Schaeffer, J., He, X. (2025) Mandarin non-interrogative wh-words distinguish between children with Developmental Language Disorder and Language-Impaired autistic children.

Language Acquisition, Vol. 32 (pp 574-597)

Article | https://doi.org/10.1080/10489223.2024.2371594 | UvA-DARE

Huang, Xuan, Burgoyne, J.A., Honing, H. (2022) What We Remember is the Prototypical: Pop Music in China from the 1970s to 2010s.

Poster | UvA-DARE

Huang, Xuan, Burgoyne, J.A., Honing, H. (2022) The Structure of Musical Preferences Using Chinese Samples.

Paper | UvA-DARE

Huang, Xuan, Burgoyne, J.A., Honing, H. (2023) What makes Chinese music memorable to the Chinese? The relationship between familiarity and recognition.

Abstract | UvA-DARE

Huguet Cabot, P.-L., Abadi, D., Fischer, A., Shutova, E. (2021) Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions.

In Merlo, P. Tiedemann, J. Tsarfaty, R. (Eds.), The 16th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2021 : proceedings of the conference : April 19-23, 2021 (pp 1921-1945). Association for Computational Linguistics.

Huguet Cabot, P.-L., Dankers, V., Abadi, D., Fischer, A., Shutova, E. (2020) The Pragmatics behind Politics: Modelling Metaphor, Framing and Emotion in Political Discourse.

In Cohn, T. He, Y. Liu, Y. (Eds.), Findings of the Association for Computational Linguistics. Findings of ACL: EMNLP 2020: 16-20 November, 2020 (pp 4479-4488). The Association for Computational Linguistics.

Huizing, D., Schäfer, G. (2021) The Traveling k-Median Problem: Approximating Optimal Network Coverage.

In Koenemann, J. Peis, B. (Eds.), Approximation and Online Algorithms: 19th International Workshop, WAOA 2021, Lisbon, Portugal, September 6–10, 2021 : revised selected papers (pp 80-98) (Lecture Notes in Computer Science, Vol. 12982). Springer.

Huizing, D., van der Mei, R., Schäfer, G., Bhulai, S. (2022) The enriched median routing problem and its usefulness in practice.

Computers & Industrial Engineering, Vol. 168

Article | https://doi.org/10.1016/j.cie.2022.108063 | UvA-DARE

Hulvej Rod , N., Broadbent, A., Hulvej Rod , M., Russo, F., Arah , O.A., Stronks , K. (2023) Complexity in epidemiology and public health. Studying and acting on complex health problems through a mix of epidemiological methods and dat.

Epidemiology

Article | UvA-DARE

Hupkes, D., Bod, R. (2015) Methods for Part-of-Speech Tagging 17th-Century Dutch.

Poster | UvA-DARE

Hupkes, D., Bod, R. (2015) Using Parallel Data to Improve Part-of-speech Tagging of 17th Century Dutch.

Abstract | UvA-DARE

Hupkes, D., Bod, R. (2016) POS-tagging of Historical Dutch.

In Calzolari, N. Choukri, K. Declerck, T. Goggi, S. Grobelnik, M. Maegaard, B. Mariani, J. Mazo, H. Moreno, A. Odijk, J. Piperidis, S. (Eds.), LREC 2016 : Tenth International Conference on Language Resources and Evaluation: May 23-28, 2016, Grand Hotel Bernardin Conference Center, Portorož, Slovenia (pp 77-82). European Language Resources Association (ELRA).

Hupkes, D., Bouwmeester, S., Fernández, R. (2018) Analysing the potential of seq-to-seq models for incremental interpretation in task-oriented dialogue.

In Linzen, T. Chrupała, G. Alishahi, A. (Eds.), The 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP: EMNLP 2018 : proceedings of the First Workshop : November 1, 2018, Brussels, Belgium (pp 165–174). The Association for Computational Linguistics.

Hupkes, D., Giulianelli, M., Dankers, V., Artetxe, M., Elazar, Y., Pimentel, T., Christodoulopoulos, C., Lasri, K., Saphra, N., Sinclair, A., Ulmer, D., Schottmann, F., Batsuren, K., Sun, K., Sinha, K., Khalatbari, L., Ryskina, M., Frieske, R., Cotterell, R., Jin, Z. (2022) State-of-the-art generalisation research in NLP: A taxonomy and review.

ArXiv.

Preprint | https://doi.org/10.48550/arXiv.2210.03050 | UvA-DARE

Hupkes, D., Giulianelli, M., Dankers, V., Artetxe, M., Elazar, Y., Pimentel, T., Christodoulopoulos, C., Lasri, K., Saphra, N., Sinclair, A., Ulmer, D., Schottmann, F., Batsuren, K., Sun, K., Sinha, K., Khalatbari, L., Ryskina, M., Frieske, R., Cotterell, R., Jin, Z. (2023) A taxonomy and review of generalization research in NLP.

Nature Machine Intelligence, Vol. 5 (pp 1161-1174)

Article | https://doi.org/10.48550/arXiv.2210.03050 | UvA-DARE

Hupkes, D., Singh, Anand Kumar, Korrel, K., Kruszewski, G., Bruni, E. (2019) Learning compositionally through attentive guidance.

Poster | UvA-DARE