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Dr. A.C. (Andrew) Yates

Faculty of Science
Informatics Institute
Visiting address
  • Science Park 904
Postal address
  • Postbus 94323
    1090 GH Amsterdam
Contact details
Social media
  • Publications

    2022

    • 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

    2021

    • 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 Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (pp. 4636–4650). ACL. 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

    2021

    • 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.
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