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Results: 130
Number of items: 130
  • Open Access
    Azzopardi, L., Clarke, C. L. A., Kantor, P., Mitra, B., Trippas, J. R., Ren, Z., Aliannejadi, M., Arabzadeh, N., Chandrasekar, R., de Rijke, M., Eustratiadis, P., Hersh, W., Huang, J., Kanoulas, E., Kareem, J., Li, Y., Lupart, S., Mekonnen, K. A., Roegiest, A., ... Zhao, Y. (2024). Report on the Search Futures Workshop at ECIR 2024. SIGIR Forum, 58(1). https://doi.org/10.1145/3687273.3687288
  • 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
    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
    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
    Abbasiantaeb, Z., Yuan, Y., Kanoulas, E., & Aliannejadi, M. (2024). Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions. In WSDM '24: Proceedings of the 17th ACM International Conference on Web Search and Data Mining : March 4-8, 2024, Merida, Mexico (pp. 8-17). Association for Computing Machinery. https://doi.org/10.1145/3616855.3635856
  • 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
    Huang, J.-H., Zhu, H., Shen, Y., Rudinac, S., Pacces, A. M., & Kanoulas, E. (2024). A Novel Evaluation Framework for Image2Text Generation. In C. Siro, M. Aliannejadi, H. A. Rahmani, N. Craswell, C. L. A. Clarke, G. Faggioli, B. Mitra, P. Thomas, & E. Yilmaz (Eds.), Proceedings of The First Workshop on Large Language Models for Evaluation in Information Retrieval (LLM4Eval 2024): co-located with 10th International Conference on Online Publishing (SIGIR 2024) : Washington D.C., USA, July 18, 2024 (pp. 51-65). Article 4 (CEUR Workshop Proceedings; Vol. 3752). CEUR-WS.
  • 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
  • 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
    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
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