Open Access
| Issue |
ITM Web Conf.
Volume 78, 2025
International Conference on Computer Science and Electronic Information Technology (CSEIT 2025)
|
|
|---|---|---|
| Article Number | 04018 | |
| Number of page(s) | 8 | |
| Section | Foundations and Frontiers in Multimodal AI, Large Models, and Generative Technologies | |
| DOI | https://doi.org/10.1051/itmconf/20257804018 | |
| Published online | 08 September 2025 | |
- Z. Liu et al., “A review of research on the illusion problem of large language models,” Journal of Software, vol. 36, no. 3, pp. 1152–1185, Dec. 2024 [Google Scholar]
- Z. Xu, S. Jain, and M. Kankanhalli, “Hallucination is Inevitable: An Innate Limitation of Large Language Models,” arXiv.org, Jan. 22, 2024 [Google Scholar]
- L. Huang et al., “A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions,” ACM transactions on office information systems, vol. 43, no. 2, Nov. 2024 [Google Scholar]
- H. Sun et al., “MoralDial: a Framework to Train and Evaluate Moral Dialogue Systems via Moral Discussions,” Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, vol. 1, Jan. 2023 [Google Scholar]
- L. Feng, F. Tung, H. Hajimirsadeghi, Y. Bengio, and M. O. Ahmed, “Memory Efficient Neural Processes via Constant Memory Attention Block,” arXiv.org, 2023 [Google Scholar]
- F. Zhou et al., “TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data,” Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Jan. 2022 [Google Scholar]
- X. Yang, “Exploring External Knowledge for Accurate modeling of Visual and Language Problems,” arXiv.org, 2023 [Google Scholar]
- Y. J. Kim, B. Kwak, Y. Kim, Reinald Kim Amplayo, S. Hwang, and J. Yeo, “Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning,” Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 2244–2257, Jan. 2022 [Google Scholar]
- P. G. Szilagyi et al., “Text vs Patient Portal Messaging to Improve Influenza Vaccination Coverage,” JAMA Internal Medicine, vol. 184, no. 5, pp. 519–519, May 2024 [Google Scholar]
- T.-L. Wu et al., “SIMMC-VR: A Task-oriented Multimodal Dialog Dataset with Situated and Immersive VR Streams,” Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, vol. 1, Jan. 2023 [Google Scholar]
- A. Karunakaran and K. Spekkens, “A Bigger Cloud 9? New HI Observations of the RELHIC Candidate M94-Cloud 9,” arXiv.org, 2024 [Google Scholar]
- OpenAI, “GPT-4 Technical Report,” arXiv:2303.08774 [cs], Mar. 2023 [Google Scholar]
- R. Cardone, S. Padhy, S. Black, S. Cleveland, and J. Stubbs, “A Decentralized Authorization and Security Framework for Distributed Research Workflows,” arXiv.org, 2023 [Google Scholar]
- S. Narayan, Y. Zhao, J. Maynez, G. Simoes, V. Nikolaev, and R. McDonald, “Planning with Learned Entity Prompts for Abstractive Summarization,” arXiv.org, 2021 [Google Scholar]
- Y.-Z. Song, Y.-S. Chen, L. Wang, and Hong-Han Shuai, “General then Personal: Decoupling and Pre-training for Personalized Headline Generation,” Transactions of the Association for Computational Linguistics, vol. 11, pp. 1588–1607, Jan. 2023 [Google Scholar]
- Y. Tao, A. Hiatt, E. Haake, A. J. Jetter, and A. Agrawal, “When Context Leads but Parametric Memory Follows in Large Language Models,” Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 4034–4058, Jan. 2024 [Google Scholar]
- T. Zhao, S. Tian, J. Daly, M. Geiger, M. Jia, and J. Zhang, “Information Retrieval and Classification of Real-Time Multi-Source Hurricane Evacuation Notices,” arXiv.org, 2024 [Google Scholar]
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