GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content
This paper presents a novel approach for detecting ChatGPT-generated vs.
human-written text using language models. To this end, we first collected and
released a pre-processed dataset named OpenGPTText, which consists of rephrased
content generated using ChatGPT. We then designed, implemented, and trained two
different models for text classification, using Robustly Optimized BERT
Pretraining Approach (RoBERTa) and Text-to-Text Transfer Transformer (T5),
respectively. Our models achieved remarkable results, with an accuracy of over
97% on the test dataset, as evaluated through various metrics. Furthermore, we
conducted an interpretability study to showcase our model's ability to extract
and differentiate key features between human-written and ChatGPT-generated
text. Our findings provide important insights into the effective use of
language models to detect generated text.
6462dfc1960c80d19c66d43d
Yutian Chen
claimed_verified
2025-07-13T07:31:34.037Z
65bf190cf629068c7f73ced0
https://cdn-avatars.huggingface.co/v1/production/uploads/65bf190cf629068c7f73ced0/4EcW7AS7HMQITtiUcJM2-.jpeg
Yutian Chen
user
YutianChen
6462dfc1960c80d19c66d43e
Hao Kang
6462dfc1960c80d19c66d43f
Vivian Zhai
6462dfc1960c80d19c66d440
Liangze Li
6462dfc1960c80d19c66d441
Rita Singh
6462dfc1960c80d19c66d442
Bhiksha Ramakrishnan
claimed_verified
2023-05-16T15:32:01.825Z
644898876ffed6ece102a856
/avatars/eb5df5b95d8f2adc70056fe71e7b4e1e.svg
Bhiksha Raj
user
bhiksha
GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content
This paper presents a novel approach for detecting ChatGPT-generated vs.
human-written text using language models. To this end, we first collected and
released a pre-processed dataset named OpenGPTText, which consists of rephrased
content generated using ChatGPT. We then designed, implemented, and trained two
different models for text classification, using Robustly Optimized BERT
Pretraining Approach (RoBERTa) and Text-to-Text Transfer Transformer (T5),
respectively. Our models achieved remarkable results, with an accuracy of over
97% on the test dataset, as evaluated through various metrics. Furthermore, we
conducted an interpretability study to showcase our model's ability to extract
and differentiate key features between human-written and ChatGPT-generated
text. Our findings provide important insights into the effective use of
language models to detect generated text.
A novel approach using RoBERTa and T5 models detects ChatGPT-generated text with over 97% accuracy on the OpenGPTText dataset.
RoBERTa T5 language models text classification interpretability study