Evaluating the Efficacy of Hybrid Deep Learning Models in Distinguishing AI-Generated Text
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Abstract (arXiv)
My research investigates the use of cutting-edge hybrid deep learning models to accurately differentiate between AI-generated text and human writing. I applied a robust methodology, utilising a carefully selected dataset comprising AI and human texts from various sources, each tagged with instructions. Advanced natural language processing techniques facilitated the analysis of textual features. Combining sophisticated neural networks, the custom model enabled it to detect nuanced differences between AI and human content.
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References · 4
- 2017Attention Is All You Needcited by 60,106
- 2020Language Models are Few-Shot Learnerscited by 32,320
- 2020Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlationcited by 422
- 2019Towards Debiasing Fact Verification Modelscited by 143
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