24 citations · 68 across the 6 of their papers we have counts for
6 papers
HateClipSeg: A Segment-Level Annotated Dataset for Fine-Grained Hate Video Detection
Han Wang, Zhuoran Wang, Roy Ka-Wei Lee
Detecting hate speech in videos remains challenging due to the complexity of multimodal content and the lack of fine-grained annotations in existing datasets. We present HateClipSe…
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video Detection
Han Wang, Rui Yang Tan, Roy Ka-Wei Lee
Detecting hate speech in online content is essential to ensuring safer digital spaces. While significant progress has been made in text and meme modalities, video-based hate speech…
MultiHateClip: A Multilingual Benchmark Dataset for Hateful Video Detection on YouTube and Bilibili
Han Wang, Tan Rui Yang, Usman Naseem +1
Hate speech is a pressing issue in modern society, with significant effects both online and offline. Recent research in hate speech detection has primarily centered on text-based m…
MemeCraft: Contextual and Stance-Driven Multimodal Meme Generation
Han Wang, Roy Ka-Wei Lee
Online memes have emerged as powerful digital cultural artifacts in the age of social media, offering not only humor but also platforms for political discourse, social critique, an…
Prompting Large Language Models for Topic Modeling
Han Wang, Nirmalendu Prakash, Nguyen Khoi Hoang +3
Topic modeling is a widely used technique for revealing underlying thematic structures within textual data. However, existing models have certain limitations, particularly when dea…
PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Models
Nirmalendu Prakash, Han Wang, Nguyen Khoi Hoang +2
The proliferation of social media has given rise to a new form of communication: memes. Memes are multimodal and often contain a combination of text and visual elements that convey…