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Results: 46
Number of items: 46
  • Open Access
    Li, C., Yates, A., Macavaney, S., He, B., & Sun, Y. (2024). PARADE: Passage Representation Aggregation for Document Reranking. ACM Transactions on Information Systems, 42(2), Article 36. https://doi.org/10.1145/3600088
  • Open Access
    Rajapakse, T. C., Yates, A., & de Rijke, M. (2024). Negative Sampling Techniques for Dense Passage Retrieval in a Multilingual Setting. In SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 14-18, 2024, Washington, DC, USA (pp. 575-584). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657854
  • 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
    Khandel, P., Yates, A., Varbanescu, A.-L., de Rijke, M., & Pimentel, A. (2024). Distillation vs. Sampling for Efficient Training of Learning to Rank Models. In ICTIR '24: Proceedings of the 2024 ACM SIGIR International Conference on the Theory of Information Retrieval : July 13, 2024 Washington, DC, USA (pp. 51-60). The Association for Computing Machinery. https://doi.org/10.1145/3664190.3672527
  • Open Access
    Lei, Y., Cao, Y., Zhou, T., Shen, T., & Yates, A. (2024). Corpus-Steered Query Expansion with Large Language Models. 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. 2, pp. 393-401). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-short.34
  • Open Access
    Farrell, M. J., Le Guillarme, N., Brierley, L., Hunter, B., Scheepens, D., Willoughby, A., Yates, A., & Mideo, N. (2024). The changing landscape of text mining: a review of approaches for ecology and evolution. Proceedings of the Royal Society B: Biological Sciences, 291(2027), Article 20240423. https://doi.org/10.1098/rspb.2024.0423
  • Open Access
    Bleeker, M. J. R. (2024). Multi-modal learning algorithms for sequence modeling and representation learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Nguyen, T., MacAvaney, S., & Yates, A. (2023). Adapting Learned Sparse Retrieval for Long Documents. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 1781-1785). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591943
  • Open Access
    Pal, V., Yates, A., Kanoulas, E., & de Rijke, M. (2023). MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), The 61st Conference of the Association for Computational Linguistics: Proceedings of the Conference : ACL 2023 : July 9-14, 2023 (Vol. 1, pp. 6322–6334). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.acl-long.348
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