论文标题
Naughtyformer：变压器了解进攻性幽默
The Naughtyformer: A Transformer Understands Offensive Humor
论文作者
论文摘要
笑话是故意写的，很有趣，但并非所有笑话都是相同的。有些笑话可能适合幼儿园的教室，但其他笑话最适合更成熟的受众。尽管最近的工作在文本中显示出令人印象深刻的结果，但在这里我们研究了检测幽默亚型的更细微的任务，尤其是较小的无辜品种。为此，我们介绍了一个从Reddit过滤的小说笑话数据集，并使用称为NaughtyFormer的填充变压器解决了亚型分类任务。此外，我们表明，与最先进的方法相比，我们的模型在检测笑话的攻击性方面要好得多。
Jokes are intentionally written to be funny, but not all jokes are created the same. Some jokes may be fit for a classroom of kindergarteners, but others are best reserved for a more mature audience. While recent work has shown impressive results on humor detection in text, here we instead investigate the more nuanced task of detecting humor subtypes, especially of the less innocent variety. To that end, we introduce a novel jokes dataset filtered from Reddit and solve the subtype classification task using a finetuned Transformer dubbed the Naughtyformer. Moreover, we show that our model is significantly better at detecting offensiveness in jokes compared to state-of-the-art methods.
