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Results: 9
Number of items: 9
  • Open Access
    Tan, S., & Monz, C. (2025). ReMedy: Learning Machine Translation Evaluation from Human Preferences with Reward Modeling. In C. Christodoulopoulos, T. Chakraborty, C. Rose, & V. Peng (Eds.), The 2025 Conference on Empirical Methods in Natural Language Processing : Proceedings of the Conference: EMNLP 2025 : November 4-9, 2025 (pp. 4370-4387). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-main.217
  • Open Access
    Tan, S., & Monz, C. (2025). Simple Test Time Scaling for Machine Translation: Kaze-MT at the WMT25 General Translation Task. 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. 651–656). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.wmt-1.40
  • 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
    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
    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
  • Tan, S., & Monz, C. (2023). ZS-NMT-Variations, EC40 Multilingual Machine Translation Dataset/Benchmark [Data set]. GitHub. https://github.com/Smu-Tan/ZS-NMT-Variations.git
  • Open Access
    Tan, S., & Monz, C. (2023). Towards a Better Understanding of Variations in Zero-Shot Neural Machine Translation Performance. 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. 13553–13568). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.836
  • Open Access
    Liao, B., Tan, S., & Monz, C. (2023). Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning. In Thirty-seventh Annual Conference on Neural Information Processing Systems OpenReview. https://openreview.net/forum?id=J8McuwS3zY
  • Open Access
    Wu, D., Tan, S., Stap, D., Araabi, A., & Monz, C. (2023). UvA-MT’s Participation in the WMT 2023 General Translation Shared Task. In P. Koehn, B. Haddow, T. Kocmi, & C. Monz (Eds.), Eighth Conference on Machine Translation: WMT 2023 : December 6-7, 2023 (pp. 175–180). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2310.09946, https://doi.org/10.18653/v1/2023.wmt-1.17
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