6 papers · 1 filter
SEAHateCheck: Functional Tests for Detecting Hate Speech in Low-Resource Languages of Southeast Asia
Ri Chi Ng, Aditi Kumaresan, Yujia Hu +1
Hate speech detection relies heavily on linguistic resources, which are primarily available in high-resource languages such as English and Chinese, creating barriers for researcher…
HateXScore: A Metric Suite for Evaluating Reasoning Quality in Hate Speech Explanations
Yujia Hu, Roy Ka-Wei Lee
Hateful speech detection is a key component of content moderation, yet current evaluation frameworks rarely assess why a text is deemed hateful. We introduce \textsf{HateXScore}, a…
Toxicity Red-Teaming: Benchmarking LLM Safety in Singapore's Low-Resource Languages
Yujia Hu, Ming Shan Hee, Preslav Nakov +1
The advancement of Large Language Models (LLMs) has transformed natural language processing; however, their safety mechanisms remain under-explored in low-resource, multilingual se…
InstructAV: Instruction Fine-tuning Large Language Models for Authorship Verification
Yujia Hu, Zhiqiang Hu, Chun-Wei Seah +1
Large Language Models (LLMs) have demonstrated remarkable proficiency in a wide range of NLP tasks. However, when it comes to authorship verification (AV) tasks, which involve dete…
ToxiCloakCN: Evaluating Robustness of Offensive Language Detection in Chinese with Cloaking Perturbations
Yunze Xiao, Yujia Hu, Kenny Tsu Wei Choo +1
Detecting hate speech and offensive language is essential for maintaining a safe and respectful digital environment. This study examines the limitations of state-of-the-art large l…
Who Wrote it and Why? Prompting Large-Language Models for Authorship Verification
Chia-Yu Hung, Zhiqiang Hu, Yujia Hu +1
Authorship verification (AV) is a fundamental task in natural language processing (NLP) and computational linguistics, with applications in forensic analysis, plagiarism detection,…