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Results: 1,025
Number of items: 1,025
  • 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
    Hager, P., Deffayet, R., Renders, J.-M., Zoeter, O., & de Rijke, M. (2024). Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset. 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. 1546-1556). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657892
  • Open Access
    Sprangers, O. R. (2024). Efficient and accurate forecasting in large-scale settings. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
    Meng, C., Arabzadeh, N., Askari, A., Aliannejadi, M., & de Rijke, M. (2024). Ranked List Truncation for Large Language Model-based Re-Ranking. 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. 141-151). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657864
  • 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
    Siro, C., Aliannejadi, M., & de Rijke, M. (2024). Context Does Matter: Implications for Crowdsourced Evaluation Labels in Task-Oriented Dialogue Systems. In K. Duh, H. Gomez, & S. Bethard (Eds.), Findings of the Association for Computational Linguistics: NAACL 2024: Findings: Findings 2024 : June 16-21, 2024 (pp. 1258–1273). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-naacl.80
  • Open Access
    Siro, C., Aliannejadi, M., & de Rijke, M. (2024). Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMs. 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. 1952-1962). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657712
  • Open Access
    Kersbergen, B., Sprangers, O., Kootte, F., Guha, S., de Rijke, M., & Schelter, S. (2024). Etude - Evaluating the Inference Latency of Session-Based Recommendation Models at Scale. In 2024 IEEE 40th International Conference on Data Engineering: ICDE 2024 : 13-17 May 2024, Utrecht, Netherlands : proceedings (pp. 5177-5183). IEEE Computer Society. https://doi.org/10.1109/icde60146.2024.00389
  • Open Access
    Li, M. (2024). Repetition and exploration in recommendation. [Thesis, fully internal, Universiteit van Amsterdam].
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