collaborators

9 papers

cs.CR2026

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…

cs.CR2026

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…

cs.CL2026

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…

cs.CR2026

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…

cs.CL2026

Patients Speak, AI Listens: LLM-based Analysis of Online Reviews Uncovers Key Drivers for Urgent Care Satisfaction

Xiaoran Xu, Zhaoqian Xue, Chi Zhang +7

Investigating the public experience of urgent care facilities is essential for promoting community healthcare development. Traditional survey methods often fall short due to limite…

cs.CY2025

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…