1 citations · 1 across the 4 of their papers we have counts for
4 papers
P-PatchDiff: Progressive Patch Diffusion Models for Low-light Image Enhancement
Ruoyu Guo, Haonan Zhong, Maurice Pagnucco +1
Recent advancements in low-light image enhancement have leveraged diffusion models for their strong ability to generate perceptually realistic, detailed images. Patch diffusion mod…
FAIRT2V: Training-Free Debiasing for Text-to-Video Diffusion Models
Haonan Zhong, Wei Song, Tingxu Han +3
Text-to-video (T2V) diffusion models have achieved rapid progress, yet their demographic biases, particularly gender bias, remain largely unexplored. We present FairT2V, a training…
Help or Hurdle? Rethinking Model Context Protocol-Augmented Large Language Models
Wei Song, Haonan Zhong, Ziqi Ding +2
The Model Context Protocol (MCP) enables large language models (LLMs) to access external resources on demand. While commonly assumed to enhance performance, how LLMs actually lever…
A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services
Hongsheng Hu, Shuo Wang, Jiamin Chang +5
The right to be forgotten requires the removal or "unlearning" of a user's data from machine learning models. However, in the context of Machine Learning as a Service (MLaaS), retr…