3 papers
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…