Big claims, low outcomes: fact checking ChatGPT’s efficacy in handling linguistic creativity and ambiguity

Author:

Qamar Md. Tauseef1ORCID,Yasmeen Juhi1ORCID,Pathak Sanket Kumar2,Sohail Shahab Saquib3ORCID,Madsen Dag Øivind4ORCID,Rangarajan Mithila5

Affiliation:

1. School of Advanced Sciences and Languages, VIT Bhopal University, Kothrikalan, Sehore, MP, India

2. Mihup Communications Pvt. Ltd, Kolkata, India

3. School of Computing Science and Engineering, VIT Bhopal University, Kothrikalan, Sehore, MP, India

4. USN School of Business, University of South-Eastern Norway, Hønefoss, Norway

5. Department of English, School of Literature and Languages, St. Joseph’s University, Bengaluru, India

Publisher

Informa UK Limited

Reference20 articles.

1. Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?

2. Language (Technology) is Power: A Critical Survey of “Bias” in NLP

3. Borji A. (2023). A categorical archive of ChatGPT failures. arXiv preprint arXiv:2302.03494.

4. Cai Z. G. Haslett D. A. Duan X. Wang S. & Pickering M. J. (2023). Does ChatGPT resemble humans in language use?. arXiv preprint arXiv:2303.08014.

5. How trustworthy is ChatGPT? The case of bibliometric analyses

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