8 citations · 20 across the 15 of their papers we have counts for
15 papers
Automating Steering for Safe Multimodal Large Language Models
Lyucheng Wu, Mengru Wang, Ziwen Xu +4
Recent progress in Multimodal Large Language Models (MLLMs) has unlocked powerful cross-modal reasoning abilities, but also raised new safety concerns, particularly when faced with…
ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark
Kangwei Liu, Siyuan Cheng, Bozhong Tian +7
Large language models (LLMs) have been increasingly applied to automated harmful content detection tasks, assisting moderators in identifying policy violations and improving the ov…
VPI-Bench: Visual Prompt Injection Attacks for Computer-Use Agents
Tri Cao, Bennett Lim, Yue Liu +7
Computer-Use Agents (CUAs) with full system access enable powerful task automation but pose significant security and privacy risks due to their ability to manipulate files, access…
LookAhead Tuning: Safer Language Models via Partial Answer Previews
Kangwei Liu, Mengru Wang, Yujie Luo +7
Fine-tuning enables large language models (LLMs) to adapt to specific domains, but often compromises their previously established safety alignment. To mitigate the degradation of m…
ReLearn: Unlearning via Learning for Large Language Models
Haoming Xu, Ningyuan Zhao, Liming Yang +7
Current unlearning methods for large language models usually rely on reverse optimization to reduce target token probabilities. However, this paradigm disrupts the subsequent token…
PhishIntel: Toward Practical Deployment of Reference-Based Phishing Detection
Yuexin Li, Hiok Kuek Tan, Qiaoran Meng +6
Phishing is a critical cyber threat, exploiting deceptive tactics to compromise victims and cause significant financial losses. While reference-based phishing detectors (RBPDs) hav…
Automated Phishing Detection Using URLs and Webpages
Huilin Wang, Bryan Hooi
Phishing detection is a critical cybersecurity task that involves the identification and neutralization of fraudulent attempts to obtain sensitive information, thereby safeguarding…
Multimodal Large Language Models for Phishing Webpage Detection and Identification
Jehyun Lee, Peiyuan Lim, Bryan Hooi +1
To address the challenging problem of detecting phishing webpages, researchers have developed numerous solutions, in particular those based on machine learning (ML) algorithms. Amo…
PhishAgent: A Robust Multimodal Agent for Phishing Webpage Detection
Tri Cao, Chengyu Huang, Yuexin Li +4
Phishing attacks are a major threat to online security, exploiting user vulnerabilities to steal sensitive information. Various methods have been developed to counteract phishing,…
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection
Yuexin Li, Chengyu Huang, Shumin Deng +5
Phishing attacks have inflicted substantial losses on individuals and businesses alike, necessitating the development of robust and efficient automated phishing detection approache…
Towards A Unified View of Answer Calibration for Multi-Step Reasoning
Shumin Deng, Ningyu Zhang, Nay Oo +1
Large Language Models (LLMs) employing Chain-of-Thought (CoT) prompting have broadened the scope for improving multi-step reasoning capabilities. We generally divide multi-step rea…
Multimodal Graph Learning for Generative Tasks
Minji Yoon, Jing Yu Koh, Bryan Hooi +1
Multimodal learning combines multiple data modalities, broadening the types and complexity of data our models can utilize: for example, from plain text to image-caption pairs. Most…
Prompt-Based Zero- and Few-Shot Node Classification: A Multimodal Approach
Yuexin Li, Bryan Hooi
Multimodal data empowers machine learning models to better understand the world from various perspectives. In this work, we study the combination of \emph{text and graph} modalitie…
SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres
Shumin Deng, Shengyu Mao, Ningyu Zhang +1
Event-centric structured prediction involves predicting structured outputs of events. In most NLP cases, event structures are complex with manifold dependency, and it is challengin…
Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graph
Shumin Deng, Chengming Wang, Zhoubo Li +11
Business Knowledge Graphs (KGs) are important to many enterprises today, providing factual knowledge and structured data that steer many products and make them more intelligent. De…