Search results
Results: 58
Number of items: 58
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Choenni, R., Garrette, D., & Shutova, E. (2023). How do languages influence each other? Studying cross-lingual data sharing during LM fine-tuning. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 13244-13257). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.818 -
Starace, G., Papakostas, K., Choenni, R., Panagiotopoulos, A., Rosati, M., Leidinger, A., & Shutova, E. (2023). Probing LLMs for Joint Encoding of Linguistic Categories. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing : Findings of the Association for Computational Linguistics: EMNLP 2023: December 6-10, 2023 (pp. 7158-7179). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.476 -
Choenni, R., Garrette, D., & Shutova, E. (2023). Cross-Lingual Transfer with Language-Specific Subnetworks for Low-Resource Dependency Parsing. Computational Linguistics, 49(3), 613-641. https://doi.org/10.1162/coli_a_00482 -
Zhang, Z., Yannakoudakis, H., Zhen, X., & Shutova, E. (2023). CK-Transformer: Commonsense Knowledge Enhanced Transformers for Referring Expression Comprehension. In A. Vlachos, & I. Augenstein (Eds.), The 17th Conference of the European Chapter of the Association for Computational Linguistics : Findings of EACL 2023: EACL 2023 : May 2-6, 2023 (pp. 2586-2596). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-eacl.196 -
Langedijk, A., Dankers, V., Lippe, P., Bos, S., Cardenas Guevara, B., Yannakoudakis, H., & Shutova, E. (2022). Meta-learning for fast cross-lingual adaptation in dependency parsing. In S. Muresan, P. Nakov, & A. Villavicencio (Eds.), The 60th Annual Meeting of the Association for Computational Linguistics: ACL 2022 : proceedings of the conference : May 22-27, 2022 (Vol. 1, pp. 8503–8520). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2104.04736, https://doi.org/10.18653/v1/2022.acl-long.582 -
Choenni, R., & Shutova, E. (2022). Investigating language relationships in multilingual sentence encoders through the lens of linguistic typology. Computational Linguistics, 48(3), 635–672. https://doi.org/10.1162/coli_a_00444 -
Srivastava, A., Siro, C., Shutova, E., Jumelet, J., ter Hoeve, M., Giulianelli, M., Lewis, M., Schubert, M., Tong, X., & BIG-bench authors (2022). Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2206.04615 -
Czinczoll, T., Yannakoudakis, H., Mishra, P., & Shutova, E. (2022). Scientific and Creative Analogies in Pretrained Language Models. In Y. Goldberg, Z. Kozareva, & Y. Zhang (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2022: Conference on Empirical Methods in Natural Language Processing (EMNLP), Abu Dhabi, United Arab Emirates, 7-11 December 2022 (pp. 2094-2100). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.findings-emnlp.153 -
Djokic, V. G., Shutova, E., & Fiebrink, R. (2021). MetaVR: Understanding metaphors in the mind and relation to emotion through immersive, spatial interaction. In CHI '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems : May 8-13, 2021, online virtual conference (originally, Yokohama, Japan) Article 185 Association for Computing Machinery. https://doi.org/10.1145/3411763.3451565
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Tong, X., Shutova, E., & Lewis, M. (2021). Recent advances in neural metaphor processing: A linguistic, cognitive and social perspective. In K. Toutanova, A. Rumshisky, L. Zettlemoyer, D. Hakkani-Tur, I. Beltagy, S. Bethard, R. Cotterell, T. Chakraborty, & Y. Zhou (Eds.), The 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL-HLT 2021 : proceedings of the conference : June 6-11, 2021 (pp. 4673-4686). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.naacl-main.372
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