198 citations · 484 across the 22 of their papers we have counts for
5 papers · 1 filter
On the Risk of Evidence Pollution for Malicious Social Text Detection in the Era of LLMs
Herun Wan, Minnan Luo, Zhixiong Su +2
Evidence-enhanced detectors present remarkable abilities in identifying malicious social text. However, the rise of large language models (LLMs) brings potential risks of evidence…
Disentangled Noisy Correspondence Learning
Zhuohang Dang, Minnan Luo, Jihong Wang +6
Cross-modal retrieval is crucial in understanding latent correspondences across modalities. However, existing methods implicitly assume well-matched training data, which is impract…
How Do Social Bots Participate in Misinformation Spread? A Comprehensive Dataset and Analysis
Herun Wan, Minnan Luo, Zihan Ma +2
Social media platforms provide an ideal environment to spread misinformation, where social bots can accelerate the spread. This paper explores the interplay between social bots and…
DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection
Herun Wan, Shangbin Feng, Zhaoxuan Tan +3
Large language models are limited by challenges in factuality and hallucinations to be directly employed off-the-shelf for judging the veracity of news articles, where factual accu…
What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection
Shangbin Feng, Herun Wan, Ningnan Wang +3
Social media bot detection has always been an arms race between advancements in machine learning bot detectors and adversarial bot strategies to evade detection. In this work, we b…