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Results: 5
Number of items: 5
  • Open Access
    Savolainen, O., Amjad, D. E. N., & Petcu, R. (2025). Interpreting Multilingual and Document-Length Sensitive Relevance Computations in Neural Retrieval Models through Axiomatic Causal Interventions. In SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 13-18, 2025, Padua, Italy (pp. 3255-3264). Association for Computing Machinery. https://doi.org/10.1145/3726302.3730327
  • Open Access
    Podolak, J., Perić, L., Janićijević, M., & Petcu, R. (2025). Beyond Reproducibility: Advancing Zero-shot LLM Reranking Efficiency with Setwise Insertion. In SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 13-18, 2025, Padua, Italy (pp. 3205-3213). Association for Computing Machinery. https://doi.org/10.1145/3726302.3730323
  • Open Access
    van Marken, C., & Petcu, R. (2025). Reproducing and Extending Causal Insights Into Term Frequency Computation in Neural Rankers. In SIGIR-AP 2025: Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region : December 7-10, 2025, Xi'an, China (pp. 189-198). Association for Computing Machinery. https://doi.org/10.1145/3767695.3769507
  • Open Access
    Askari, A., Petcu, R., Meng, C., Aliannejadi, M., Abolghasemi, A., Kanoulas, E., & Verberne, S. (2025). SOLID: Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking Dialogs. In L. Chiruzzo, A. Ritter, & L. Wang (Eds.), Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics : Proceedings of the Conference : Findings: NAACL 2025 : April 29-May 4, 2025 (pp. 6390–6410). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.findings-naacl.357
  • 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
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