Papers by Kenny Choo
ToxiCloakCN: Evaluating Robustness of Offensive Language Detection in Chinese with Cloaking Perturbations (2024.emnlp-main)
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| Challenge: | Existing large language models struggle with systematically perturbed data designed to evade detection mechanisms. |
| Approach: | They propose a large language model with homophonic substitutions and emoji transformations to test their models' robustness against cloaking perturbations. |
| Outcome: | The proposed model underperforms in detecting offensive content when perturbations are applied to Chinese language datasets. |