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Results: 46
Number of items: 46
  • 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
    Fang, Y. (2023). Machine learning tasks and representations for heterogeneous information networks. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Bénédict, G., Zhang, R., Metzler, D., Yates, A., Deffayet, R., Hager, P., & Jullien, S. (2023). Report on the 1st Workshop on Generative Information Retrieval (Gen-IR 2023) at SIGIR 2023. SIGIR Forum, 57(2), Article 13. https://doi.org/10.1145/3642979.3642995
  • Lin, J., Nogueira, R., & Yates, A. (2022). Pretrained Transformers for Text Ranking: BERT and Beyond. (Synthesis Lectures on Human Language Technologies; Vol. 53). Springer. https://doi.org/10.2200/S01123ED1V01Y202108HLT053
  • Open Access
    Naseri, S., Dalton, J., Yates, A., & Allan, J. (2022). CEQE to SQET: A study of contextualized embeddings for query expansion. Information Retrieval Journal, 25(2), 184–208. https://doi.org/10.1007/s10791-022-09405-y
  • Open Access
    Farrell, M. J., Brierley, L., Willoughby, A., Yates, A., & Mideo, N. (2022). Past and future uses of text mining in ecology and evolution. Proceedings of the Royal Society B: Biological Sciences, 289(1975), Article 20212721. https://doi.org/10.1098/rspb.2021.2721
  • Open Access
    Nguyen, T., Yates, A., Zirikly, A., Desmet, B., & Cohan, A. (2022). Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires. In S. Muresan, P. Nakov, & A. Villavicencio (Eds.), The 60th Annual Meeting of the Association for Computational Linguistics: ACL 2022 : proceedings of the conference : May 22-27, 2022 (Vol. 1, pp. 8446-8459). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2204.10432, https://doi.org/10.18653/v1/2022.acl-long.578
  • Open Access
    Pradeep, R., Liu, Y., Zhang, X., Li, Y., Yates, A., & Lin, J. (2022). Squeezing Water from a Stone: A Bag of Tricks for Further Improving Cross-Encoder Effectiveness for Reranking. In M. Hagen, S. Verberne, C. Macdonald, C. Seifert, K. Balog, K. Nørvåg, & V. Setty (Eds.), Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022 : proceedings (Vol. I, pp. 655–670). (Lecture Notes in Computer Science; Vol. 13185). Springer. https://doi.org/10.1007/978-3-030-99736-6_44
  • Open Access
    Khandel, P., Markov, I., Yates, A., & Varbanescu, A.-L. (2022). ParClick: A Scalable Algorithm for EM-based Click Models. In WWW'22: proceedings of the ACM Web Conference 2022 : April 25-29, 2022, VIrtual Event, Lyon, France (pp. 392-400). Association for Computing Machinery. https://doi.org/10.1145/3485447.3511967
  • Open Access
    Krasakis, A. M., Yates, A., & Kanoulas, E. (2022). Zero-shot Query Contextualization for Conversational Search. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 1880–1884). The Association for Computing Machinery. https://doi.org/10.48550/arXiv.2204.10613, https://doi.org/10.1145/3477495.3531769
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