mlsanityData to 14 Oct 2026

No offence, Bert -- I insult only humans! Multiple addressees sentence-level attack on toxicity detection neural network

arXiv 2310.13099 ↗First posted 19 Oct 2023cs.CL cs.AI cs.LGcited by 0

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Abstract (arXiv)

We introduce a simple yet efficient sentence-level attack on black-box toxicity detector models. By adding several positive words or sentences to the end of a hateful message, we are able to change the prediction of a neural network and pass the toxicity detection system check. This approach is shown to be working on seven languages from three different language families. We also describe the defence mechanism against the aforementioned attack and discuss its limitations.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 7 references that are in the map. First posted on arXiv 19 Oct 2023.

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References · 2

  1. 2017Adversarial Examples for Evaluating Reading Comprehension Systemscited by 571
  2. 2018Robust Machine Comprehension Models via Adversarial Trainingcited by 44

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