most cited"Pull or Not to Pull?'': Investigating Moral Biases in Leading Large Language Models Across Ethical Dilemmas

2 citations · 3 across the 9 of their papers we have counts for

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cs.CR2026

PUFFERDOS: Efficient and Effective Attack String Generation for Regular Expression Denial of Service Vulnerabilities

Shangzhi Xu, Ziqi Ding, Xiao Cheng +5

ReDoS attacks constitute a critical class of resource-exhaustion vulnerabilities. In such attacks, adversaries exploit the pathological worst-case execution behavior of regular exp…

cs.CR2026

Membership Inference Attacks Against Video Large Language Models

Wei Song, Yuxin Cao, Ziqi Ding +3

Video large language models (VideoLLMs) are increasingly trained or instruction-tuned on large-scale video--text corpora collected from heterogeneous sources, raising an immediate…

cs.CR2025

A Rusty Link in the AI Supply Chain: Detecting Evil Configurations in Model Repositories

Ziqi Ding, Qian Fu, Junchen Ding +3

Recent advancements in large language models (LLMs) have spurred the development of diverse AI applications from code generation and video editing to text generation; however, AI s…

cs.CR2025★ 1 cited

IllusionCAPTCHA: A CAPTCHA based on Visual Illusion

Ziqi Ding, Gelei Deng, Yi Liu +4

CAPTCHAs have long been essential tools for protecting applications from automated bots. Initially designed as simple questions to distinguish humans from bots, they have become in…

cs.CR2025

TombRaider: Entering the Vault of History to Jailbreak Large Language Models

Junchen Ding, Jiahao Zhang, Yi Liu +3

Warning: This paper contains content that may involve potentially harmful behaviours, discussed strictly for research purposes. Jailbreak attacks can hinder the safety of Large Lan…