EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 204 (2024) SHS Web Conf., 204 (2024) 03012 References
Open Access
Issue
SHS Web Conf.
Volume 204, 2024
1st International Graduate Conference on Digital Policy and Governance Sustainability (DiGeS-Grace 2024)
Article Number 03012
Number of page(s) 11
Section Smart City and Smart Society
DOI https://doi.org/10.1051/shsconf/202420403012
Published online 25 November 2024
  1. OpenAI, GPT-4 Technical Report, arXiv [cs.CL], Mar. 2023. DOI: 10.48550/arXiv.2303.08774. [Google Scholar]
  2. L. Ouyang, J. Wu, X. Jiang, et al., Training language models to follow instructions with human feedback, arXiv [cs.CL], Mar. 2022. DOI: 10.48550/arXiv.2203.02155. [Google Scholar]
  3. J. Liu, C.S. Xia, Y. Wang, L. Zhang, Is your code generated by ChatGPT really correct? Rigorous evaluation of Large Language Models for code generation, Proc. 37th Int. Conf. Neural Information Processing Systems, 37, 21558–21572 (2024). DOI: 10.48550/arXiv.2305.01210. [Google Scholar]
  4. G. Orrù, A. Piarulli, C. Conversano, A. Gemignani, Human-like Problem-Solving Abilities in Large Language Models Using ChatGPT, Front. Artif. Intell. 6, 1199350 (2023). DOI: 10.3389/frai.2023.1199350. [CrossRef] [Google Scholar]
  5. S. Feng, C.Y. Park, Y. Liu, Y. Tsvetkov, From pretraining data to language models to downstream tasks: Tracking the trails of political biases leading to unfair NLP models, Proc. 61st Annu. Meet. Assoc. Comput. Linguist. 1, 11737–11762 (2023). DOI: 10.48550/arXiv.2305.08283. [CrossRef] [Google Scholar]
  6. MainichiShimbun, Osaka Prefecture corrects AI conversation service after being criticized for ‘praising a specific political party’, Mainichi Shimbun, [Online]. Available: https://mainichi.jp/articles/20230913/k00/00m/040/390000c. [Accessed: Apr. 12, 2024]. [Google Scholar]
  7. T.H. Kung, M. Cheatham, A. Medenilla, et al., Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models, PLOS Digit. Health 2, 198 (2023). DOI: 10.1371/journal.pdig.0000198. [Google Scholar]
  8. D. Baidoo-Anu, L. Owusu Ansah, Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning, J. Aircr. 7, 52–62 (2023). DOI: 10.2139/ssrn.4337484. [Google Scholar]
  9. S. Panda, N. Kaur, Exploring the viability of ChatGPT as an alternative to traditional chatbot systems in library and information centers, Libr. Hi Tech News 40, 22–25 (2023). DOI: 10.1108/LHTN-02-2023-0032. [CrossRef] [Google Scholar]
  10. A.B. Mbakwe, I. Lourentzou, L.A. Celi, et al., ChatGPT passing USMLE shines a spotlight on the flaws of medical education, PLOS Digit. Health 2, 205 (2023). DOI: 10.1371/journal.pdig.0000205. [Google Scholar]
  11. H.H. Thorp, ChatGPT is fun, but not an author, Science 379, 313 (2023). DOI: 10.1126/science.adg7879. [CrossRef] [Google Scholar]
  12. B. Lund, W. Ting, Chatting about ChatGPT: How May AI and GPT Impact Academia and Libraries?, Libr. Hi Tech News 40, 3, 26–29 (2023). DOI: 10.1108/LHTN-01-2023-0009. [CrossRef] [Google Scholar]
  13. D. Rozado, The Political Biases of ChatGPT, Soc. Sci. 12, 148 (2023). DOI: 10.3390/socsci12030148. [CrossRef] [Google Scholar]
  14. J. Rutinowski, S. Franke, J. Endendyk, et al., The Self-Perception and Political Biases of ChatGPT, arXiv [cs.CY], Apr. 2023. DOI: 10.48550/arXiv.2304.07333. [Google Scholar]
  15. A. Testa, M. Cinque, A. Coronato, G. De Pietro, J.C. Augusto, Heuristic Strategies for Assessing Wireless Sensor Network Resiliency: An Event-Based Formal Approach, J. Heuristics, 21, 145175 (2015). DOI: 10.1007/s10732-014-9258-x. [CrossRef] [Google Scholar]
  16. Senkyo.com, Vote matching, Political party version 2023 - Senkyo.com, [Online]. Available: https://election.go2senkyo.com/votematches_political_party2023/. [Accessed: Apr. 12, 2024]. [Google Scholar]
  17. K. Inoshita, Quantitative Analysis of Political Party Understanding and the Impact of Political Bias through ChatGPT (Experiment Results), Apr. 2024. [Online]. Available: https://figshare.com/articles/dataset/Quantitative_Analysis_of_Political_Party_Understanding_and_the_Impact_of_Political_Bias_through_ChatGPT_Experiment_Results_/25596180. [Accessed: Apr. 13, 2024]. [Google Scholar]
  18. M. Guo, Z. Dai, D. Vrandečić, R. Al-Rfou, and N. Calzolari, F. Béchet, P. Blache, et al. (eds), Wiki- 40B: Multilingual Language Model Dataset, in Proc. 12th Lang. Resour. Eval. Conf., pp. 2440–2452 (2020). [Google Scholar]
  19. Range3/cc100-ja, Datasets: range3/cc100-ja - range3/cc100-ja, 2023. [Online]. Available: https://huggingface.co/datasets/range3/cc100-ja/tree/main. [Accessed: Apr. 12, 2024]. [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.