8 papers
Large Language Models and Social Media Information Integrity: Opportunities, Challenges, and Research Directions
Junjie Xiong, Zhengyuan Jiang, Xiaoran Xu +7
Large Language Models (LLMs) have emerged as powerful tools that impact information integrity on social media platforms. This comprehensive review examines the dual role of LLMs in…
COGNITION: From Evaluation to Defense against Multimodal LLM CAPTCHA Solvers
Junyu Wang, Changjia Zhu, Yuanbo Zhou +4
This paper studies how multimodal large language models (MLLMs) undermine the security guarantees of visual CAPTCHA. We identify the attack surface where an adversary can cheaply a…
LLM-as-a-Reviewer: Benchmarking Their Ability, Divergence, and Prompt Injection Resistance as Paper Reviewers
Lingyao Li, Junjie Xiong, Changjia Zhu +5
Large language models (LLMs) are increasingly used in academic peer review, yet their reliability, alignment with human judgment, and robustness to adversarial attacks remain poorl…
Prompt Overflow: What the Guardrail Inspects Is Not What the Model Infers
Yuanbo Zhou, Changjia Zhu, Junyu Wang +5
Guardrail models (a.k.a. safety checkers) are widely deployed to screen user inputs before they reach large language models (LLMs), serving as a primary defense against prompt inje…
Disciplined Diffusion: Text-to-Image Diffusion Model against NSFW Generation
Chi Zhang, Changjia Zhu, Xiaowen Li +2
Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can generate offensive or disturb…
When Your Reviewer is an LLM: Biases, Divergence, and Prompt Injection Risks in Peer Review
Changjia Zhu, Junjie Xiong, Renkai Ma +3
Peer review is the cornerstone of academic publishing, yet the process is increasingly strained by rising submission volumes, reviewer overload, and expertise mismatches. Large lan…