Loading Now

Summary of Styloai: Distinguishing Ai-generated Content with Stylometric Analysis, by Chidimma Opara


StyloAI: Distinguishing AI-Generated Content with Stylometric Analysis

by Chidimma Opara

First submitted to arxiv on: 16 May 2024

Categories

  • Main: Computation and Language (cs.CL)
  • Secondary: Artificial Intelligence (cs.AI)

     Abstract of paper      PDF of paper


GrooveSquid.com Paper Summaries

GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!

Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
The proposed StyloAI model uses 31 stylometric features to identify AI-generated texts by applying a Random Forest classifier on two multi-domain datasets. The model achieves high accuracy rates of 81% and 98% on the test sets of the AuTextification dataset and the Education dataset, respectively, surpassing existing state-of-the-art models.
Low GrooveSquid.com (original content) Low Difficulty Summary
The researchers have developed a new way to tell if text is written by a human or a computer. They created a model called StyloAI that uses special features to figure out what makes AI-generated text different from human-written text. The model was tested on two big datasets and did really well, showing that it can accurately spot AI-generated text.

Keywords

» Artificial intelligence  » Random forest