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Results: 160
Number of items: 160
  • Open Access
    Liao, B., Herold, C., Khadivi, S., & Monz, C. (2024). ApiQ: Finetuning of 2-Bit Quantized Large Language Model. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), The 2024 Conference on Empirical Methods in Natural Language Processing : Proceedings of the Conference: EMNLP 2024 : November 12-16, 2024 (pp. 20996-21020). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.emnlp-main.1168
  • Open Access
    Tan, S., Wu, D., Stap, D., Aycock, S., & Monz, C. (2024). UvA-MT’s Participation in the WMT24 General Translation Shared Task. In B. Haddow, T. Kocmi, P. Koehn, & C. Monz (Eds.), Ninth Conference on Machine Translation : Proceedings of the Conference: WMT 2024 : November 15-16, 2024 (pp. 176-184). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.wmt-1.11
  • Open Access
    Araabi, A. (2024). Exploring solutions for low-resource neural machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Kocmi, T., Avramidis, E., Bawden, R., Bojar, O., Dvorkovich, A., Federmann, C., Fishel, M., Freitag, M., Gowda, T., Grundkiewicz, R., Haddow, B., Karpinska, M., Koehn, P., Marie, B., Monz, C., Murray, K., Nagata, M., Popel, M., Popović, M., ... Zouhar, V. (2024). Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet. In B. Haddow, T. Kocmi, P. Koehn, & C. Monz (Eds.), Ninth Conference on Machine Translation : Proceedings of the Conference: WMT 2024 : November 15-16, 2024 (pp. 1–46). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.wmt-1.1
  • Open Access
    Meng, Y., & Monz, C. (2024). Disentangling the Roles of Target-side Transfer and Regularization in Multilingual Machine Translation. In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics : Proceedings of the Conference: EACL 2024 : March 17-22, 2024 (Vol. 1, pp. 1828–1840). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-long.110
  • Open Access
    Wu, D., Lei, Y., Yates, A., & Monz, C. (2024). Representational Isomorphism and Alignment of Multilingual Large Language Models. In J. Sälevä, & A. Owodunni (Eds.), The 4th Workshop on Multilingual Representation Learning : proceedings of the workshop: MRL 2024 : November 16, 2024 (pp. 293-297). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.mrl-1.24
  • Open Access
    Wu, D., Lei, Y., Yates, A., & Monz, C. (2024). Representational Isomorphism and Alignment of Multilingual Large Language Models. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), The 2024 Conference on Empirical Methods in Natural Language Processing : Findings of EMNLP 2024: EMNLP 2024 : November 12-16, 2024 (pp. 14074-14085). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-emnlp.823
  • Open Access
    Wu, D., Tan, S., Meng, Y., Stap, D., & Monz, C. (2024). How Far can 100 Samples Go? Unlocking Zero-Shot Translation with Tiny Multi-Parallel Data. In L.-W. Ku, A. Martins, & V. Srikumar (Eds.), The 62nd Annual Meeting of the Association for Computational Linguistics : Findings of the Association for Computational Linguistics: ACL 2024: ACL 2024 : August 11-16, 2024 (pp. 15092-15108). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-acl.896
  • Open Access
    Stap, D., Hasler, E., Byrne, B., Monz, C., & Tran, K. (2024). The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities. 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. 6189-6206). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-long.336
  • Open Access
    Tan, S., Wu, D., & Monz, C. (2024). Neuron Specialization: Leveraging Intrinsic Task Modularity for Multilingual Machine Translation. In Y. Al-Onaizan, M. Bansal, & Y.-N. Chen (Eds.), The 2024 Conference on Empirical Methods in Natural Language Processing : Proceedings of the Conference: EMNLP 2024 : November 12-16, 2024 (pp. 6506-6527). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.emnlp-main.374
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