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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM60755

Text Marker -Text Evaluation Tool for Marking AI and Real Knowledge-based Entries and Responses

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM60755

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem60755

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

D

D.Sreya

KV

K.Srivalli Varshini

KA

K. Ashrith

AP

Asst. Prof.K.Priyanka

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Abstract

– In today’s world, because of how quickly artificial intelligence writing tools are getting better, it’s now hard to tell whether something was written by AI or a person. This makes things complicated for students writing papers, for checking if information is true, and for making sure work is original. A system for identifying AI versus human writing has been built to automatically sort text into one of these two groups. It’s built around a RoBERTa transformer model – this is the main part that decides what something is, and it’s very good at grasping the meanings of words and how language works. People using it can type or copy and paste text into a webpage, and the system will analyze it immediately. It’s been created using Python’s many options and put on Railway(deployment tools) so anyone can get to it online easily. It reliably and quickly says whether text is AI or human, and how sure it is of its answer, which is helpful for school, research and looking at content in general.

KEYWORDS

Artificial Intelligence RoBERTa Natural Language Processing Text Classification AI-Generated Text

Cite This Article

D.Sreya, K.Srivalli Varshini, K. Ashrith, Asst. Prof.K.Priyanka, "Text Marker -Text Evaluation Tool for Marking AI and Real Knowledge-based Entries and Responses," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026. https://doi.org/10.55041/ijsrem60755

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Publication Date

4/20/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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