使用透明解决方案和语言专业知识的自动内容审核

Veronika Solopova
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引用次数: 0

摘要

自从基于变形金刚的模型出现以来,透明度和准确性之间的权衡一直是NLP社区的一个热门问题。致力于道德和透明的自动内容审核(ACM),我的目标是找到仍然与实施语言专业知识相关的地方。我表明,基于语言知识的透明统计模型仍然具有竞争力,而语言特征还有许多其他有用的应用。
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Automated Content Moderation Using Transparent Solutions and Linguistic Expertise
Since the dawn of Transformer-based models, the trade-off between transparency and accuracy has been a topical issue in the NLP community. Working towards ethical and transparent automated content moderation (ACM), my goal is to find where it is still relevant to implement linguistic expertise. I show that transparent statistical models based on linguistic knowledge can still be competitive, while linguistic features have many other useful applications.
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