On the definition of toxicity in NLP

Sergey Berezin, Reza Farahbakhsh, Noel Crespi
10/3/2023
cs.CLcs.AIcs.LG

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Abstract

The fundamental problem in toxicity detection task lies in the fact that the toxicity is ill-defined. This causes us to rely on subjective and vague data in models' training, which results in non-robust and non-accurate results: garbage in - garbage out. This work suggests a new, stress-level-based definition of toxicity designed to be objective and context-aware. On par with it, we also describe possible ways of applying this new definition to dataset creation and model training.

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Cite this paper

@article{berezin2023definition,
  title  = {On the definition of toxicity in NLP},
  author = {Sergey Berezin and Reza Farahbakhsh and Noel Crespi},
  year   = {2023},
  eprint = {2310.02357},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.02357v3}
}

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