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Results: 134
Number of items: 134
  • Open Access
    Nonkes, N., Agaronian, S., Kanoulas, E., & Petcu, R. (2024). Leveraging Graph Structures to Detect Hallucinations in Large Language Models. In D. Ustalov, Y. Gao, A. Panchenko, E. Tutubalina, I. Nikishina, A. Ramesh, A. Sakhovskiy, R. Usbeck, G. Penn, & M. Valentino (Eds.), Proceedings of TextGraphs-17: Graph-based Methods for Natural Language Processing : The 62nd Annual Meeting of the Association of Computational Linguistics: TextGraphs @ ACL 2024 : August 15, 2024 (pp. 93-104). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.textgraphs-1.7
  • Open Access
    Huang, J.-H., Yang, C.-C., Shen, Y., Pacces, A. M., & Kanoulas, E. (2024). Optimizing Numerical Estimation and Operational Efficiency in the Legal Domain through Large Language Models. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 4554-4562). Association for Computing Machinery. https://doi.org/10.1145/3627673.3680025
  • Open Access
    Capurro, C., Provatorova, V., Hendriksen, M., Kanoulas, E., & Dupré, S. (2024). Digital Art Technical Sources for the Netherlands: Integration and Improvement of Sources on Glass for a Sustainable Future – Art DATIS. In B. R. Haverkort, A. de Jongste, P. van Kuilenburg, & R. D. Vromans (Eds.), Commit2Data Article 9 (OpenAccess Series in Informatics; Vol. 124). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASIcs.Commit2Data.9
  • Open Access
    Sidiropoulos, G., & Kanoulas, E. (2024). Improving the Robustness of Dense Retrievers Against Typos via Multi-Positive Contrastive Learning. 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. III, pp. 297–305). (Lecture Notes in Computer Science; Vol. 14610). Springer. https://doi.org/10.1007/978-3-031-56063-7_21
  • Open Access
    Cheirmpos, G., Tabatabaei, S. A., Kanoulas, E., & Tsatsaronis, G. (2024). Benchmarking Named Entity Recognition Approaches for Extracting Research Infrastructure Information from Text. In G. Nicosia, V. Ojha, E. La Malfa, G. La Malfa, P. M. Pardalos, & R. Umeton (Eds.), Machine Learning, Optimization, and Data Science: 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023 : revised selected papers (Vol. I, pp. 131–141). (Lecture Notes in Computer Science; Vol. 14505). Springer. https://doi.org/10.1007/978-3-031-53969-5_11
  • Open Access
    Zou, J., Sun, A., Long, C., & Kanoulas, E. (2024). Knowledge-Enhanced Conversational Recommendation via Transformer-Based Sequential Modeling: ACM Transactions on Information Systems. ACM Transactions on Information Systems, 42(6), Article 162. https://doi.org/10.1145/3677376
  • Open Access
    Krasakis, A. M., Yates, A., & Kanoulas, E. (2024). Contextualizing and Expanding Conversational Queries without Supervision. ACM Transactions on Information Systems, 42(3), Article 77. https://doi.org/10.1145/3632622
  • Open Access
    Ma, H., Zhou, J., Aliannejadi, M., Kanoulas, E., Bin, Y., & Yang, Y. (2024). Ask or Recommend: An Empirical Study on Conversational Product Search. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 3927-3931). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679875
  • Open Access
    Zhu, H., Huang, J.-H., Rudinac, S., & Kanoulas, E. (2024). Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Models. In Proceedings of the 14th Annual ACM International Conference on Multimedia Retrieval (ICMR'24): Phuket, Thailand, June 10-14, 2024 (pp. 978-987). Association for Computing Machinery. https://doi.org/10.1145/3652583.3658032
  • Open Access
    Soudani, H., Kanoulas, E., & Hasibi, F. (2024). Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge. In SIGIR-AP '24: Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region : December 9-12, 2024, Tokyo, Japan (pp. 12-22). Association for Computing Machinery. https://doi.org/10.1145/3673791.3698415
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