Papers by Portia Cooper
The Lies Characters Tell: Utilizing Large Language Models to Normalize Adversarial Unicode Perturbations (2025.findings-acl)
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| Challenge: | Homoglyphs are visually homogeneous to Latin letters and are used to mask offensive content. |
| Approach: | They propose two methods to normalize homoglyphs by replacing non-Latin characters with a delimiter and using large language models to determine which characters should be replaced with Latin letters. |
| Outcome: | The proposed methods normalize homoglyphs by replacing non-Latin characters with a delimiter and prompting large language models to "fill in the blanks" the authors found that the proposed methods produced normalized text with an average cosine similarity score of 0.91 to the original tweets and 0.96 to the tweets using the direct method. |
Hiding in Plain Sight: Tweets with Hate Speech Masked by Homoglyphs (2023.findings-emnlp)
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| Challenge: | Currently, there are almost 150,000 Unicode characters, which presents extensive substitution possibilities. |
| Approach: | They develop a character substitution scraping method to collect hate speech . they use an annotated dataset with 1,281 non-Latin characters to scrape out offensive words . |
| Outcome: | The proposed method can detect hate speech with annotated data, but it performs poorly in a zero-shot setting. |