Open Access
| Issue |
ITM Web Conf.
Volume 76, 2025
Harnessing Innovation for Sustainability in Computing and Engineering Solutions (ICSICE-2025)
|
|
|---|---|---|
| Article Number | 05013 | |
| Number of page(s) | 11 | |
| Section | Emerging Technologies & Computing | |
| DOI | https://doi.org/10.1051/itmconf/20257605013 | |
| Published online | 25 March 2025 | |
- Pandiarajan, S., Yazhmozhi, V. M., & Praveen Kumar, P. (2018). Semantic search engine using natural language processing. SpringerLink. researchgate.net [Google Scholar]
- Ghali, M.-K., Farrag, A., Won, D., & Jin, Y. (2024). Enhancing knowledge retrieval with in-context learning and semantic search through generative AI. arXiv preprint arXiv:2406.09621. arxiv.org [Google Scholar]
- Zhu, Y., Yuan, H., Wang, S., Liu, J., Liu, W., Deng, C., Chen, H., Dou, Z., & Wen, J.-R. (2023). Large language models for information retrieval: A survey. arXiv preprint arXiv:2308.07107. arxiv.org [Google Scholar]
- Sarkar, D. (2024). Navigating the knowledge sea: Planet-scale answer retrieval using LLMs. arXiv preprint arXiv:2402.05318. arxiv.org [Google Scholar]
- Jia, R., Zhang, B., Rodríguez Méndez, S. J., & Omran, P. G. (2024). Leveraging large language models for semantic query processing in a scholarly knowledge graph. arXiv preprint arXiv:2405.15374. arxiv.org [Google Scholar]
- Lewis, P., Oguz, B., Riedel, S., & Lewis, M. (2020). Retrieval-augmented generation for knowledge-intensive NLP tasks. Advances in Neural Information Processing Systems, 33, 9459–9474. arxiv.org [Google Scholar]
- Alqahtani, A., & Alzahrani, A. (2021). Natural language processing (NLP) application for classifying and managing tacit knowledge in revolutionizing AI-driven libraries. SpringerLink. researchgate.net [Google Scholar]
- Zelikman, E., Ma, W. A., Tran, J. E., Yang, D., Yeatman, J. D., & Haber, N. (2023). Generating and evaluating tests for K-12 students with language model simulations: A case study on sentence reading efficiency. Empirical Methods in Natural Language Processing (EMNLP). nlp.stanford.edu [Google Scholar]
- Navigli, R., Pinto, M., Silvestri, P., Rotondi, D., Ciciliano, S., Scire, A. (2024). NounAtlas: Filling the gap in nominal semantic role labeling. Proceedings of ACL, 16245–16258. [Google Scholar]
- Tedeschi, S., Bos, J., Declerck, T., Hajic, J., Hershcovich, D., Hovy, E. H., Koller, A., Krek, S., Schockaert, S., Sennrich, R., Shutova, E., Wang, W. Y. (2023). What's the meaning of superhuman performance in today's NLU? Proceedings of ACL 2023, 12471–12491. [Google Scholar]
- Conia, S., Bacciu, A., & Navigli, R. (2021). Unifying cross-lingual semantic role labeling with heterogeneous linguistic resources. Proceedings of NAACL-HLT 2021, 338–351. [Google Scholar]
- Campagna, G., Semnani, S., Kearns, R., Sato, L. J., Xu, S., & Lam, M. (2022). A few-shot semantic parser for Wizard-of-Oz dialogues with the precise ThingTalk representation. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 1–15. nlp.stanford.edu [Google Scholar]
- Lassance, C., & Clinchant, S. (2022). Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery. [Google Scholar]
- Nguyen, T., Hendriksen, M., Yates, S., & de Rijke, M. (2024). Advances in Information Retrieval. Springer Nature Switzerland. [Google Scholar]
- Zhuang, S., & Zuccon, G. (2021). Fast passage re-ranking with contextualized exact term matching and efficient passage expansion. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 1–10. [Google Scholar]
- Zhao, T., Lu, X., & Lee, K. (2020). SPARTA: Efficient open-domain question answering via sparse transformer matching retrieval. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 1001–1010. [Google Scholar]
- Liu, J., & Callan, J. (2020). Proceedings of the Web Conference 2020. ACM. [Google Scholar]
- Nguyen, T., MacAvaney, S., Yates, A., & de Rijke, M. (2023). Advances in Information Retrieval. Springer Nature Switzerland. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.