2 citations · 7 across the 18 of their papers we have counts for
9 papers · 1 filter
ToxiLab: How Well Do Open-Source LLMs Generate Synthetic Toxicity Data?
Zheng Hui, Zhaoxiao Guo, Hang Zhao +5
Effective toxic content detection relies heavily on high-quality and diverse data, which serve as the foundation for robust content moderation models. Synthetic data has become a c…
NovAScore: A New Automated Metric for Evaluating Document Level Novelty
Lin Ai, Ziwei Gong, Harshsaiprasad Deshpande +4
The rapid expansion of online content has intensified the issue of information redundancy, underscoring the need for solutions that can identify genuinely new information. Despite…
CREAM: Comparison-Based Reference-Free ELO-Ranked Automatic Evaluation for Meeting Summarization
Ziwei Gong, Lin Ai, Harshsaiprasad Deshpande +5
Large Language Models (LLMs) have spurred interest in automatic evaluation methods for summarization, offering a faster, more cost-effective alternative to human evaluation. Howeve…
PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
Jiateng Liu, Lin Ai, Zizhou Liu +6
Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the…
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances
Zehui Wu, Ziwei Gong, Lin Ai +3
Emotion recognition in speech is a challenging multimodal task that requires understanding both verbal content and vocal nuances. This paper introduces a novel approach to emotion…
Defending Against Social Engineering Attacks in the Age of LLMs
Lin Ai, Tharindu Kumarage, Amrita Bhattacharjee +12
The proliferation of Large Language Models (LLMs) poses challenges in detecting and mitigating digital deception, as these models can emulate human conversational patterns and faci…
What Makes A Video Radicalizing? Identifying Sources of Influence in QAnon Videos
Lin Ai, Yu-Wen Chen, Yuwen Yu +3
In recent years, radicalization is being increasingly attempted on video-sharing platforms. Previous studies have been proposed to identify online radicalization using generic soci…
Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension
Lin Ai, Zheng Hui, Zizhou Liu +1
Machine Reading Comprehension (MRC) poses a significant challenge in the field of Natural Language Processing (NLP). While mainstream MRC methods predominantly leverage extractive…
QASE Enhanced PLMs: Improved Control in Text Generation for MRC
Lin Ai, Zheng Hui, Zizhou Liu +1
To address the challenges of out-of-control generation in generative models for machine reading comprehension (MRC), we introduce the Question-Attended Span Extraction (QASE) modul…