Abusive language is an important issue in online communication across different platforms
and languages. Having a robust model to detect abusive instances automatically is a …

The social impact of natural language processing and its applications has received
increasing attention. In this position paper, we focus on the problem of safety for end-to-end …

Recently, social media platforms are heavily moderated to prevent the spread of online hate
speech, which is usually fertile in toxic words and is directed toward an individual or a …

Over the last several years, end-to-end neural conversational agents have vastly improved
in their ability to carry a chit-chat conversation with humans. However, these models are …

We present the first English corpus study on abusive language towards three conversational
AI systems gathered" in the wild": an open-domain social bot, a rule-based chatbot, and a …

Hate speech detection has gained increasing attention with the growing prevalence of
hateful contents. When a text contains an obvious hate word or expression, it is fairly easy to …

Despite remarkable advances that large language models have achieved in chatbots,
maintaining a non-toxic user-AI interactive environment has become increasingly critical …

Research on abusive content detection on social media has primarily focused on explicit
forms of hate speech (HS), that are often identifiable by recognizing hateful words and …

Warning: This paper contains abusive samples that may cause discomfort to readers.
Abusive language on social media reinforces prejudice against an individual or a specific …

Over the last several years, end-to-end neural conversational agents have vastly improved
their ability to carry unrestricted, open-domain conversations with humans. However, these …