Papers with machine-generated text detection methods

2 papers
IMGTB: A Framework for Machine-Generated Text Detection Benchmarking (2024.acl-demos)

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Challenge: MGTD methods are needed in many areas, such as prevention of disinformation spreading, plagiarism, impersonation and identity theft.
Approach: They propose a framework for machine-generated text detection that integrates custom methods and evaluation datasets into existing frameworks.
Outcome: The proposed framework simplifies the benchmarking of machine-generated text detection methods by easy integration of custom (new) methods and evaluation datasets.
Paraphrasing Attack Resilience of Various Machine-Generated Text Detection Methods (2025.naacl-srw)

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Challenge: Recent large-scale emergence of LLMs has left an open space for dealing with consequences, such as plagiarism or the spread of false information on the Internet.
Approach: They evaluate the parsing attack resilience of three machine-generated text detection methods and their ensembles using Random Forest classifiers.
Outcome: The proposed methods yield the strongest results, but suffer significant losses during attacks.

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