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Results: 46
Number of items: 46
  • Open Access
    Tigunova, A., Haratinezhad Torbati, G., Yates, A., & Weikum, G. (2024). STAR: Sparse Text Approach for Recommendation. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 4086–4090). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679999
  • Open Access
    Nguyen, T., Hendriksen, M., Yates, A., & de Rijke, M. (2024). Multimodal Learned Sparse Retrieval with Probabilistic Expansion Control. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald, & I. Ounis (Eds.), Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024 : proceedings (Vol. II, pp. 448–464). ( Lecture Notes in Computer Science; Vol. 14609). Springer. https://doi.org/10.48550/arXiv.2402.17535, https://doi.org/10.1007/978-3-031-56060-6_29
  • 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
    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
    Thijssen, S., Khandel, P., Yates, A., & Varbanescu, A.-L. (2024). MassiveClicks: A Massively-Parallel Framework for Efficient Click Models Training. In D. Zeinalipur, D. Blanco Heras, G. Pallis, H. Herodotou, D. Trihinas, D. Balouek, P. Diehl, T. Cojean, K. Fürlinger, M. H. Kirkeby, M. Nardelli, & P. Di Sanzo (Eds.), Euro-Par 2023: Parallel Processing Workshops: Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28-September 1, 2023 : revised selected papers (Vol. I, pp. 232–245). (Lecture Notes in Computer Science; Vol. 14351). Springer. https://doi.org/10.1007/978-3-031-50684-0_18
  • Open Access
    Li, M. (2024). Repetition and exploration in recommendation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Rus, C., Yates, A., & de Rijke, M. (2024). A Study of Pre-processing Fairness Intervention Methods for Ranking People. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald, & I. Ounis (Eds.), Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024 : proceedings (Vol. IV, pp. 336–350). (Lecture Notes in Computer Science; Vol. 14611). Springer. https://doi.org/10.1007/978-3-031-56066-8_26
  • Open Access
    Rus, C., Poerwawinata, G., Yates, A., & de Rijke, M. (2024). AnnoRank: A Comprehensive Web-Based Framework for Collecting Annotations and Assessing Rankings. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 5400-5404). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679174
  • 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
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