Detection of tortured phrases in scientific literature
Eléna Martel Martin Lentschat Cyril Labbé
This paper presents various automatic detection methods to extract so called
tortured phrases from scientific papers. These tortured phrases, e.g. flag to
clamor instead of signal to noise, are the results of paraphrasing tools used
to escape plagiarism detection. We built a dataset and evaluated several
strategies to flag previously undocumented tortured phrases. The proposed and
tested methods are based on language models and either on embeddings
similarities or on predictions of masked token. We found that an approach using
token prediction and that propagates the scores to the chunk level gives the
best results. With a recall value of .87 and a precision value of .61, it could
retrieve new tortured phrases to be submitted to domain experts for validation.