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Dr. A.C. (Andrew) Yates

Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute

  • Science Park 904
  • Postbus 94323
    1090 GH Amsterdam
  • Publicaties


    • Farrell, M. J., Brierley, L., Willoughby, A., Yates, A. C., & Mideo, N. (2022). Past and future uses of text mining in ecology and evolution. Proceedings of the Royal Society B: Biological Sciences. https://ecoevorxiv.org/c4kvq/
    • Khandel, P., Markov, I., Yates, A. C., & Varbanescu, A. L. (2022). ParClick: A Scalable Algorithm for EM-based Click Models. In WWW '22: Proceedings of the ACM Web Conference 2022 (pp. 392-400). ACM. https://doi.org/10.1145/3485447.3511967
    • Naseri, S., Dalton, J., Yates, A. C., & Allan, J. (2022). CEQE to SQET: A study of contextualized embeddings for query expansion. Information Retrieval Journal.
    • Nguyen, T. T., Yates, A. C., Zirikly, A., Desmet, B., & Cohan, A. (2022). Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 8446-8459). ACL. https://arxiv.org/pdf/2204.10432
    • Pradeep, R., Liu, Y., Zhang, X., Li, Y., Yates, A. C., & Lin, J. (2022). Squeezing Water from a Stone: A Bag of Tricks for Further Improving Cross-Encoder Effectiveness for Reranking. In 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


    • Jose, K. M., Nguyen, T. T., MacAvaney, S., Dalton, J., & Yates, A. C. (2021). DiffIR: Exploring Differences in Ranking Models' Behavior. In SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2595-2599). ACM. https://doi.org/10.1145/3404835.3462784
    • MacAvaney, S., Yates, A., Feldman, S., Downey, D., Cohan, A., & Goharian, N. (2021). Simplified Data Wrangling with ir_datasets. In SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2429-2436). ACM. https://doi.org/10.48550/arXiv.2103.02280, https://doi.org/10.1145/3404835.3463254
    • Mackie, I., Dalton, J., & Yates, A. C. (2021). How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset. In SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2335–2341). ACM. https://doi.org/10.1145/3404835.3463262
    • Nogueira, R., Lin, J., & Yates, A. C. (2021). Pretrained Transformers for Text Ranking: BERT and Beyond. Morgan & Claypool. https://doi.org/10.2200/S01123ED1V01Y202108HLT053
    • Tigunova, A., Mirza, P., Yates, A. C., & Weikum, G. (2021). PRIDE: Predicting Relationships in Conversations. In M-C. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), 2021 Conference on Empirical Methods in Natural Language Processing: EMNLP 2021 : proceedings of the conference : November 7-11, 2021 (pp. 4636–4650). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.emnlp-main.380
    • Zheng, Z., Hui, K., He, B., Han, X., Sun, L., & Yates, A. C. (2021). Contextualized query expansion via unsupervised chunk selection for text retrieval. Information Processing & Management, 58(5). https://doi.org/10.1016/j.ipm.2021.102672


    • Razniewski, S., Yates, A. C., Kassner, N., & Weikum, G. (2021). Language Models As or For Knowledge Bases. Paper presented at 4th Workshop on Deep Learning for Knowledge Graphs, DL4KG 2021, Virtual, Online.
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
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