Nov. 11, 2022, 2:15 a.m. | Jan Philip Wahle, Terry Ruas, Tomáš Foltýnek, Norman Meuschke, Bela Gipp

cs.CL updates on arXiv.org arxiv.org

Employing paraphrasing tools to conceal plagiarized text is a severe threat
to academic integrity. To enable the detection of machine-paraphrased text, we
evaluate the effectiveness of five pre-trained word embedding models combined
with machine learning classifiers and state-of-the-art neural language models.
We analyze preprints of research papers, graduation theses, and Wikipedia
articles, which we paraphrased using different configurations of the tools
SpinBot and SpinnerChief. The best performing technique, Longformer, achieved
an average F1 score of 80.99% (F1=99.68% for SpinBot and …

arxiv machine plagiarism

Senior Machine Learning Engineer

@ GPTZero | Toronto, Canada

ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)

@ HelloBetter | Remote

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Principal Data Architect - Azure & Big Data

@ MGM Resorts International | Home Office - US, NV

GN SONG MT Market Research Data Analyst 11

@ Accenture | Bengaluru, BDC7A