most citedKnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection

8 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2024★ 1 cited

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,…

cs.CL2024

Multi-party Response Generation with Relation Disentanglement

Tianhao Dai, Chengyu Huang, Lizi Liao

Existing neural response generation models have achieved impressive improvements for two-party conversations, which assume that utterances are sequentially organized. However, many…

cs.CR2024★ 8 cited

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…

cs.CL2024★ 1 cited

Training Language Models to Generate Text with Citations via Fine-grained Rewards

Chengyu Huang, Zeqiu Wu, Yushi Hu +1

While recent Large Language Models (LLMs) have proven useful in answering user queries, they are prone to hallucination, and their responses often lack credibility due to missing r…

cs.CL2022

Conversation Disentanglement with Bi-Level Contrastive Learning

Chengyu Huang, Zheng Zhang, Hao Fei +1

Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main dr…