2 citations · 3 across the 4 of their papers we have counts for
6 papers
"Pull or Not to Pull?'': Investigating Moral Biases in Leading Large Language Models Across Ethical Dilemmas
Junchen Ding, Penghao Jiang, Zihao Xu +4
As large language models (LLMs) increasingly mediate ethically sensitive decisions, understanding their moral reasoning processes becomes imperative. This study presents a comprehe…
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…
Socrates or Smartypants: Testing Logic Reasoning Capabilities of Large Language Models with Logic Programming-based Test Oracles
Zihao Xu, Junchen Ding, Yiling Lou +3
Large Language Models (LLMs) have achieved significant progress in language understanding and reasoning. Evaluating and analyzing their logical reasoning abilities has therefore be…
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…
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…
Image-Based Geolocation Using Large Vision-Language Models
Yi Liu, Junchen Ding, Gelei Deng +6
Geolocation is now a vital aspect of modern life, offering numerous benefits but also presenting serious privacy concerns. The advent of large vision-language models (LVLMs) with a…