85 citations · 225 across the 32 of their papers we have counts for
33 papers
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection
Rui Cao, Ming Shan Hee, Adriel Kuek +3
Hateful meme detection is a challenging multimodal task that requires comprehension of both vision and language, as well as cross-modal interactions. Recent studies have tried to f…
ChatGPT and Bard Responses to Polarizing Questions
Abhay Goyal, Muhammad Siddique, Nimay Parekh +9
Recent developments in natural language processing have demonstrated the potential of large language models (LLMs) to improve a range of educational and learning outcomes. Of recen…
Decoding the Underlying Meaning of Multimodal Hateful Memes
Ming Shan Hee, Wen-Haw Chong, Roy Ka-Wei Lee
Recent studies have proposed models that yielded promising performance for the hateful meme classification task. Nevertheless, these proposed models do not generate interpretable e…
TotalDefMeme: A Multi-Attribute Meme dataset on Total Defence in Singapore
Nirmalendu Prakash, Ming Shan Hee, Roy Ka-Wei Lee
Total Defence is a defence policy combining and extending the concept of military defence and civil defence. While several countries have adopted total defence as their defence pol…
Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
Lei Wang, Wanyu Xu, Yihuai Lan +4
Large language models (LLMs) have recently been shown to deliver impressive performance in various NLP tasks. To tackle multi-step reasoning tasks, few-shot chain-of-thought (CoT)…
Adapter-TST: A Parameter Efficient Method for Multiple-Attribute Text Style Transfer
Zhiqiang Hu, Roy Ka-Wei Lee, Nancy F. Chen
Adapting a large language model for multiple-attribute text style transfer via fine-tuning can be challenging due to the significant amount of computational resources and labeled d…
Evaluating GPT-3 Generated Explanations for Hateful Content Moderation
Han Wang, Ming Shan Hee, Md Rabiul Awal +2
Recent research has focused on using large language models (LLMs) to generate explanations for hate speech through fine-tuning or prompting. Despite the growing interest in this ar…
CoAIcoder: Examining the Effectiveness of AI-assisted Human-to-Human Collaboration in Qualitative Analysis
Jie Gao, Kenny Tsu Wei Choo, Junming Cao +2
While AI-assisted individual qualitative analysis has been substantially studied, AI-assisted collaborative qualitative analysis (CQA)-a process that involves multiple researchers…
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models
Zhiqiang Hu, Lei Wang, Yihuai Lan +6
The success of large language models (LLMs), like GPT-4 and ChatGPT, has led to the development of numerous cost-effective and accessible alternatives that are created by finetunin…
Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection
Md Rabiul Awal, Roy Ka-Wei Lee, Eshaan Tanwar +2
Hate speech in social media is a growing phenomenon, and detecting such toxic content has recently gained significant traction in the research community. Existing studies have expl…
Prompting for Multimodal Hateful Meme Classification
Rui Cao, Roy Ka-Wei Lee, Wen-Haw Chong +1
Hateful meme classification is a challenging multimodal task that requires complex reasoning and contextual background knowledge. Ideally, we could leverage an explicit external kn…
Are Current Task-oriented Dialogue Systems Able to Satisfy Impolite Users?
Zhiqiang Hu, Roy Kaa-Wei Lee, Nancy F. Chen
Task-oriented dialogue (TOD) systems have assisted users on many tasks, including ticket booking and service inquiries. While existing TOD systems have shown promising performance…
Predicting Hate Intensity of Twitter Conversation Threads
Qing Meng, Tharun Suresh, Roy Ka-Wei Lee +1
Tweets are the most concise form of communication in online social media, wherein a single tweet has the potential to make or break the discourse of the conversation. Online hate s…
On Explaining Multimodal Hateful Meme Detection Models
Ming Shan Hee, Roy Ka-Wei Lee, Wen-Haw Chong
Hateful meme detection is a new multimodal task that has gained significant traction in academic and industry research communities. Recently, researchers have applied pre-trained v…
Will You Dance To The Challenge? Predicting User Participation of TikTok Challenges
Lynnette Hui Xian Ng, John Yeh Han Tan, Darryl Jing Heng Tan +1
TikTok is a popular new social media, where users express themselves through short video clips. A common form of interaction on the platform is participating in "challenges", which…
Improving Text Auto-Completion with Next Phrase Prediction
Dong-Ho Lee, Zhiqiang Hu, Roy Ka-Wei Lee
Language models such as GPT-2 have performed well on constructing syntactically sound sentences for text auto-completion task. However, such models often require considerable train…
AutoChart: A Dataset for Chart-to-Text Generation Task
Jiawen Zhu, Jinye Ran, Roy Ka-wei Lee +2
The analytical description of charts is an exciting and important research area with many applications in academia and industry. Yet, this challenging task has received limited att…
Syntax Matters! Syntax-Controlled in Text Style Transfer
Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal
Existing text style transfer (TST) methods rely on style classifiers to disentangle the text's content and style attributes for text style transfer. While the style classifier play…
Disentangling Hate in Online Memes
Rui Cao, Ziqing Fan, Roy Ka-Wei Lee +2
Hateful and offensive content detection has been extensively explored in a single modality such as text. However, such toxic information could also be communicated via multimodal c…
AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection
Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee +1
Automated hate speech detection in social media is a challenging task that has recently gained significant traction in the data mining and Natural Language Processing community. Ho…
DeepHate: Hate Speech Detection via Multi-Faceted Text Representations
Rui Cao, Roy Ka-Wei Lee, Tuan-Anh Hoang
Online hate speech is an important issue that breaks the cohesiveness of online social communities and even raises public safety concerns in our societies. Motivated by this rising…
DeepStyle: User Style Embedding for Authorship Attribution of Short Texts
Zhiqiang Hu, Roy Ka-Wei Lee, Lei Wang +2
Authorship attribution (AA), which is the task of finding the owner of a given text, is an important and widely studied research topic with many applications. Recent works have sho…
Text Style Transfer: A Review and Experimental Evaluation
Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal +1
The stylistic properties of text have intrigued computational linguistics researchers in recent years. Specifically, researchers have investigated the Text Style Transfer (TST) tas…
On Analyzing Antisocial Behaviors Amid COVID-19 Pandemic
Md Rabiul Awal, Rui Cao, Sandra Mitrovic +1
The COVID-19 pandemic has developed to be more than a bio-crisis as global news has reported a sharp rise in xenophobia and discrimination in both online and offline communities. S…