12 citations · 23 across the 8 of their papers we have counts for
9 papers
Using LLMs to Detect LLM-Generated Texts: A Cross-Generation Analysis
Haiyue Yuan, Jie Guo, Weidong Qiu +3
Automated detection of LLM-generated texts (LGTs) is critical, yet dedicated detectors often struggle to generalize across domains and models. While general-purpose LLMs offer flex…
Using LLMs for Automated Privacy Policy Analysis: Prompt Engineering, Fine-Tuning and Explainability
Yuxin Chen, Peng Tang, Weidong Qiu +1
Privacy policies are widely used by digital services and often required for legal purposes. Many machine learning based classifiers have been developed to automate detection of dif…
"I know myself better, but not really greatly": How Well Can LLMs Detect and Explain LLM-Generated Texts?
Jiazhou Ji, Jie Guo, Weidong Qiu +6
Distinguishing between human- and LLM-generated texts is crucial given the risks associated with misuse of LLMs. This paper investigates detection and explanation capabilities of c…
Everyone's Privacy Matters! An Analysis of Privacy Leakage from Real-World Facial Images on Twitter and Associated User Behaviors
Yuqi Niu, Weidong Qiu, Peng Tang +5
Online users often post facial images of themselves and other people on online social networks (OSNs) and other Web 2.0 platforms, which can lead to potential privacy leakage of pe…
A Comprehensive Study on GDPR-Oriented Analysis of Privacy Policies: Taxonomy, Corpus and GDPR Concept Classifiers
Peng Tang, Xin Li, Yuxin Chen +5
Machine learning based classifiers that take a privacy policy as the input and predict relevant concepts are useful in different applications such as (semi-)automated compliance an…
PassTSL: Modeling Human-Created Passwords through Two-Stage Learning
Yangde Wang, Haozhang Li, Weidong Qiu +2
Textual passwords are still the most widely used user authentication mechanism. Due to the close connections between textual passwords and natural languages, advanced technologies…
Detecting Machine-Generated Texts: Not Just "AI vs Humans" and Explainability is Complicated
Jiazhou Ji, Ruizhe Li, Shujun Li +6
As LLMs rapidly advance, increasing concerns arise regarding risks about actual authorship of texts we see online and in real world. The task of distinguishing LLM-authored texts i…
When Graph Convolution Meets Double Attention: Online Privacy Disclosure Detection with Multi-Label Text Classification
Zhanbo Liang, Jie Guo, Weidong Qiu +2
With the rise of Web 2.0 platforms such as online social media, people's private information, such as their location, occupation and even family information, is often inadvertently…
Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation
Xin Yuan, Jie Guo, Weidong Qiu +2
Mis- and disinformation online have become a major societal problem as major sources of online harms of different kinds. One common form of mis- and disinformation is out-of-contex…