5 papers
A Unified Perspective on Adversarial Membership Manipulation in Vision Models
Ruize Gao, Kaiwen Zhou, Yongqiang Chen +1
Membership inference attacks (MIAs) aim to determine whether a specific data point was part of a model's training set, serving as effective tools for evaluating privacy leakage of…
TraceDet: Hallucination Detection from the Decoding Trace of Diffusion Large Language Models
Shenxu Chang, Junchi Yu, Weixing Wang +4
Diffusion large language models (D-LLMs) have recently emerged as a promising alternative to auto-regressive LLMs (AR-LLMs). However, the hallucination problem in D-LLMs remains un…
MESH -- Understanding Videos Like Human: Measuring Hallucinations in Large Video Models
Garry Yang, Zizhe Chen, Man Hon Wong +5
Large Video Models (LVMs) build on the semantic capabilities of Large Language Models (LLMs) and vision modules by integrating temporal information to better understand dynamic vid…
Learning Causality for Modern Machine Learning
Yongqiang Chen
In the past decades, machine learning with Empirical Risk Minimization (ERM) has demonstrated great capability in learning and exploiting the statistical patterns from data, or eve…
Beyond Pixels: Text Enhances Generalization in Real-World Image Restoration
Haoze Sun, Wenbo Li, Jiayue Liu +7
Generalization has long been a central challenge in real-world image restoration. While recent diffusion-based restoration methods, which leverage generative priors from text-to-im…