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Results: 55
Number of items: 55
  • Open Access
    Leidinger, A. J. (2025). Towards language models that benefit us all: Studies on stereotypes, robustness, and values. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Johnson, T., ter Veen, M., Choenni, R., van der Maas, H. L. J., Shutova, E., & Stevenson, C. E. (2025). Do large language models solve verbal analogies like children do? In G. Boleda, & M. Roth (Eds.), The 29th Conference on Computational Natural Language Learning (CoNLL 2025) : Proceedings of the Conference: CoNLL 2025 : July 31-August 1, 2025 (pp. 627-639). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2310.20384, https://doi.org/10.18653/v1/2025.conll-1.40
  • Open Access
    Choenni, R. M. V. (2025). Multilinguality and multiculturalism: Towards effective and inclusive neural language models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Zhang, Z. (2025). Advancing vision and language models through commonsense knowledge, efficient adaptation and transparency. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Rajaee, S., Choenni, R., Shutova, E., & Monz, C. (2025). An Empirical Analysis of Machine Translation for Expanding Multilingual Benchmarks. In B. Haddow, T. Kocmi, P. Koehn, & C. Monz (Eds.), Tenth Conference on Machine Translation : Proceedings of the Conference: WMT 2025 : November 8-9, 2025 (pp. 1-30). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.wmt-1.1
  • Verhoeven, I., Mishra, P., & Shutova, E. (2024). misinfo-general [Data set]. Harvard Dataverse. https://doi.org/10.7910/dvn/txxufn
  • Open Access
    Choenni, R., Lauscher, A., & Shutova, E. (2024). The Echoes of Multilinguality: Tracing Cultural Value Shifts during Language Model Fine-tuning. In L.-W. Ku, A. Martins, & V. Srikumar (Eds.), The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) : proceedings of the conference: ACL 2024 : August 11-16, 2024 (Vol. 1, pp. 15042-15058). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-long.803
  • Open Access
    Choenni, R., Shutova, E., & Garrette, D. (2024). Examining Modularity in Multilingual LMs via Language-Specialized Subnetworks. In K. Duh, H. Gomez, & S. Bethard (Eds.), Findings of the Association for Computational Linguistics: NAACL 2024: Findings : June 16-21, 2024 (pp. 287-301). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-naacl.21
  • Open Access
    Tong, X., Choenni, R., Lewis, M., & Shutova, E. (2024). Metaphor Understanding Challenge Dataset for LLMs. In L.-W. Ku, A. Martins, & V. Srikumar (Eds.), The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) : proceedings of the conference: ACL 2024 : August 11-16, 2024 (Vol. 1, pp. 3517-3536). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-long.193
  • Open Access
    Singh, A. K., Shutova, E., & Yannakoudakis, H. (2024). Learning New Tasks from a Few Examples with Soft-Label Prototypes. In J. Sälevä, & A. Owodunni (Eds.), The 4th Workshop on Multilingual Representation Learning : proceedings of the workshop: MRL 2024 : November 16, 2024 (pp. 215-236). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.repl4nlp-1.16
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