Analysis of ChatGPT as a Question-Answering Tool

[1] https://fireflies.ai/blog/generative-ai-or-gpt-3-apps

[2] Number of parameters in notable Artificial Intelligence

Systems, Our World in Data. [Online]. Available: https://

ourworldindata.org/grapher/artificial-intelligenceparametercount. [Accessed: 22-Mar-2023].

[3] Hughes, A. (2023). CHATGPT: Everything you need to

know about OpenAI’s GPT-4 tool, ChatGPT: Everything

you need to know about OpenAI’s GPT-4 upgrade — BBC

Science, Focus Magazine, 16-Mar-2023. [Online]. Available: https://www.sciencefocus.com/futuretechnology/gpt3 [Accessed: 22-Mar-2023].

[4] https://towardsdatascience.com/gpt-3-a-complete-overview-190232eb25fd

[5] Yu, Caiyang., Liu, Xianggen., Tang, Chenwei., Feng,

Wentao., Jiancheng GPT-NAS: Neural Architecture Search

with the Generative Pre-Trained Model.

Lv.arXiv:2305.05351v1 [cs.CV] 9 May 2023]

[6] Hendy, A., Abdelrehim, M., Sharaf, A., Raunak, V.,

Gabr, M., Matsushita, H., Kim, Y. J., Afify, M., Awadalla,

H. H. (2023). How good are gpt models at machine translation? a comprehensive evaluation, arXiv preprint

arXiv:2302.09210, 2023

[7] Mathew L. Bindu, V. (2020). A review of natural language processing techniques for sentiment analysis using pre-trained models, In: 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2020, p. 340–345.

[8] Bongini, P., Becattini, F., Del Bimbo, A. (2022). Is gpt3 all you need for visual question answering in cultural

heritage? In: Computer Vision–ECCV 2022 Workshops:

Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part

I. Springer, 2023, p. 268–281.

[9] Limna, Pongsakorn., Kraiwanit, Tanpat., Jangjarat,

Kris., KlayklungPrapasiri, Chocksathaporn, Piyawatjana

(2023). The use of ChatGPT in the digital era: Perspectives on chatbot implementation, Journal of Applied Learn-ing & Teaching. Vol.6 (1) 1-22.

[10] Cooper, K. (2021, November 1). OpenAI GPT-3: Everything you need to know. Springboard, https://

www.springboard.com/blog/data-science/machine-learning-gpt-3-open-ai

[11] Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan,

J. D., Dhariwal, P., Amodei, D. (2020). Language models

are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877-1901.

[12] Dehouche, N. (2021). Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3). Ethics

in Science and Environmental Politics, 21, 17-23

[13] Fyfe, P. (2022). How to cheat on your final paper:

Assigning AI for student writing. AI & Society, 1-11.

[14] Anson, C. M., Straume, I. (2022). Amazement and

trepidation: Implications of AI-based natural language production for the teaching of writing. Journal of Academic

Writing, 12 (1) 1-9.

[15] Anson, C. M. (2022). AI-based text generation and

the social construction of “fraudulent authorship”: A

revisitation. Composition Studies, 50, 37-46.

[16] Köbis, N., Mossink, L. D. (2021). Artificial intelligence

versus Maya Angelou: Experimental evidence that people

cannot differentiate AI-generated from human-written poetry. Computers in Human Behavior, 114, 106553

[17] Tate, T., Doroudi, S., Ritchie, D., Xu, Y. (2023). Educational research and AI-generated writing: Confronting

the coming tsunami. Pre-print. https://edarxiv.org/4mec3

[18] Moore, S., Nguyen, H. A., Bier, N., Domadia, T.,

Stamper, J. (2022). Assessing the quality of student-generated short answer questions using GPT-3. In: European

Conference on Technology Enhanced Learning (p. 243-

257). Springer.

[19] Elkins, K., Chun, J. (2020). Can GPT-3 pass a writer’s

Turing test? Journal of Cultural Analytics, 5 (2) 17212.

[20] Nguyen, H. A., Bhat, S., Moore, S., Bier, N., Stamper,

J. (2022). Towards generalized methods for automatic

question generation in educational domains. In: European

Conference on Technology Enhanced Learning p. 272-

284. Springer.

[21] Yu, Caiyang., Liu, Xianggen., Tang, Chenwei., Feng,

Wentao., Lv, Jiancheng.(GPT-NAS: Neural Architecture

Search with the Generative Pre-Trained

Model.arXiv:2305.05351v1 [cs.CV] 9 May 2023

[22] Hendy, A., Abdelrehim, M., Sharaf, A., Raunak, V.,

Gabr, M., Matsushita, H., Kim, Y. J., Afify, M. Awadalla,

H. H (2023). How good are GPT models at machine translation? a comprehensive evaluation, arXiv preprint

arXiv:2302.09210

[23] Mathew, L., Bindu, V (2020). A review of natural language processing techniques for sentiment analysis using pre-trained models, In: 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2020, p. 340–345.

[24] Bongini, P., Becattini, F. Del Bimbo, A (2022). Is gpt3 all you need for visual question answering in cultural

heritage? In: Computer Vision–ECCV 2022 Workshops:

Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part

I. Springer, 2023, p. 268–281.

[25] Li, Chenglu., Xing, Wanli. (2021). Natural Language

Generation Using Deep Learning to Support MOOC Learners. International Journal of Artificial Intelligence in Education v. 31, p.186–214.

[26] Caballé, S., Conesa, J. (2019). Conversational Agents

in Support for Collaborative Learning in MOOCs: An Analytical Review. In F. Xhafa, L. Barolli, & M. Greguš (Eds.),

Advances in Intelligent Networking and Collaborative Systems. INCoS 2018. Lecture notes on data engineering

and communications technologies (Vol. 23). Cham:

Springer.

[27] Kumar, R., Rose, C. P. (2010). Architecture for building conversational agents that support collaborative learning. IEEE Transactions on Learning Technologies, 4 (1)

21–34. https://doi.org/10.1109/TLT.2010.41

[28] Mittal, A., Vigentini, L., Djatmiko, M., Prusty, G.,

Sharma, Y., King, M. E. (2018). MOOC-O-Bot: Using

Cognitive Technologies to Extend Knowledge Support in

MOOCs. Proceedings of the 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 69–76. https://doi.org/10.1109/

tale.2018.8615453.]

[29] Shawar and Atwell Abu Shawar, B., Atwell, E. (2007).

Chatbots: Are They Really Useful? LDV-Forum Band, 22,

29-49.

[30] Indurthi, S. R., Raghu, D., Khapra, M. M., Joshi, S.

(2017). Generating natural language question-answer pairs

from a knowledge graph using a RNN-based question

generation model. In: M. Lapata, P. Blunsom, A. Koller

(Eds), Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers (pp. 376-385). Association for Computational Linguistics. https://doi.org/

10.18653/v1/e17-1036.

[31] Radford, A., Wu, J., Child, R., Luan, D., Amodei, D.,

Sutskever, I. (2019). Language models are unsupervised

multitask learners. OpenAI Blog, 1 (8) 9. Retrieved 4 Jan

2020, from http://www.persagen.com/files/misc/radford2019language.pdf

[32] Zhang, Y., Sun, S., Galley, M., Chen, Y.-C.,

Brockett, C., Gao, X., Dolan, B. (2020). DialoGPT:

Large-scale generative pre-training for conversational

response generation. In: A. Celikyilmaz, T. Wen (Eds),

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (p. 270–278). Association for Computational Linguistics. https://doi.org/

10.18653/v1/2020.acl-demos.30

[33] Eva A. M., van Dis, Bollen, Johan., Rooij, Robert

van., Zuidema, Willem., Bockting, Claudi L. (2023).

ChatGPT: five priorities for research, Nature V. 614. 224-

2266. 9 February 2023.

[34] Rich, A. S., Gureckis, T. M.(2019). Nature Mach.

Intell. 1, 174–180. 2019.

[35] Else, Holly., Gao, C. A. et al (2022). ABSTRACTS

WRITTEN BY CHATGPT FOOL SCIENTISTS by. Nature V. 613, 19 January 2023 p. 423. Preprint at bioRxiv

https://doi.org/10.1101/2022.12.23.521610.

[36] ChatGPT: five priorities for research by Eva A. M.

van Dis, Johan Bollen, Robert van Rooij, Willem Zuidema

& Claudi L. Bockting- 224-2266, Nature, Vol 614 . 9 February 2023.

[37] JOUR Kenney, Noah A Brief Analysis of the Architecture, Limitations, and Impacts of ChatGPT DO -

10.5281/zenodo.7762245 2023/03/23

[38] Zhu, Yaoming., Lu, Sidi., Zheng, Lei., Guo, Jiaxian.,

Zhang, Weinan., Wang, Jun ., Yu, Yong. (2018). Texygen:

A Benchmarking Platform for Text Generation Models.

ACM SIGIR’18, July 8-12, 2018, p. 1097-1100. Ann Arbor,

MI, USA

[39] Sallam, Malik. (2023). ChatGPT Utility in Healthcare

Education, Research, and Practice: Systematic Review

on the Promising Perspectives and Valid Concerns,

Healthcare, 11 (6) 887; https://doi.org/10.3390/

healthcare11060887