Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 160
Number of items: 160
  • 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
    Stap, D., & Monz, C. (2023). Multilingual k-Nearest-Neighbor Machine Translation. 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. 9200–9208). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.571
  • 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
  • Open Access
    Naszádi, K., Manggala, P., & Monz, C. (2023). Aligning Predictive Uncertainty with Clarification Questions in Grounded Dialog. 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. 14988–14998). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.999
  • 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., & Monz, C. (2023). Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine Translation. 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. 9749–9764). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.605
  • Open Access
    Soleimani, A., Monz, C., & Worring, M. (2023). NonFactS: NonFactual Summary Generation for Factuality Evaluation in Document Summarization. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), Findings of the Association for Computational Linguistics: ACL 2023: July 9-14, 2023 (pp. 6405-6419). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.400
  • Open Access
    Liao, B., Thulke, D., Hewavitharana, S., Ney, H., & Monz, C. (2022). Mask More and Mask Later: Efficient Pre-training of Masked Language Models by Disentangling the [MASK] Token. 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. 1478–1492). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2211.04898, https://doi.org/10.18653/v1/2022.findings-emnlp.106
  • Open Access
    Soleimani, A., Monz, C., & Worring, M. (2021). NLQuAD: A Non-Factoid Long Question Answering Data Set. In P. Merlo, J. Tiedemann, & R. Tsarfaty (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. 1245-1255). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.eacl-main.106
  • Open Access
    Ren, P., Chen, Z., Ren, Z., Kanoulas, E., Monz, C., & de Rijke, M. (2021). Conversations with Search Engines: SERP-based Conversational Response Generation. ACM Transactions on Information Systems, 39(4), Article 47. https://doi.org/10.1145/3432726
Page 4 of 16