Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11801
Title: Turquaz at Checkthat! 2024: Creating Adversarial Examples Using Genetic Algorithm
Authors: Demirok, B.
Mergen, S.
Oz, B.
Kutlu, M.
Keywords: Adversarial Examples
Credibility Assessment
Natural Language Processing
Robustness
Generative adversarial networks
Genetic algorithms
Credibility assessment
Daily tasks
Language model
Language processing
Natural language processing
Natural languages
Robustness
Second group
Splittings
Text manipulation
Adversarial machine learning
Publisher: CEUR-WS
Abstract: As we increasingly integrate artificial intelligence into our daily tasks, it is crucial to ensure that these systems are reliable and robust against adversarial attacks. In this paper, we present our participation in Task 6 of CLEF CheckThat! 2024 lab. In our work, we explore several methods, which can be grouped into two categories. The first group focuses on using a genetic algorithm to detect words and changing them via several methods such as adding/deleting words and using homoglyphs. In the second group of methods, we use large language models to generate adversarial attacks. Based on our comprehensive experiments, we pick the genetic algorithm-based model which utilizes a combination of splitting words and homoglyphs as a text manipulation method, as our primary model. We are ranked third based on both BODEGA metric and manual evaluation. © 2024 Copyright for this paper by its authors.
Description: 25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024 -- 9 September 2024 through 12 September 2024 -- Grenoble -- 201493
URI: https://hdl.handle.net/20.500.11851/11801
ISSN: 1613-0073
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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