collaborators

5 papers

cs.IR2026

Diagnosing and Repairing Citation Failures in Generative Engine Optimization

Zhihua Tian, Yuhan Chen, Yao Tang +2

Generative Engine Optimization (GEO) aims to improve content visibility in AI-generated responses. However, existing methods measure contribution-how much a document influences a r…

cs.LG2026

Understanding and Preserving Safety in Fine-Tuned LLMs

Jiawen Zhang, Yangfan Hu, Kejia Chen +7

Fine-tuning is an essential and pervasive functionality for applying large language models (LLMs) to downstream tasks. However, it has the potential to substantially degrade safety…

cs.LG2026

Safety at One Shot: Patching Fine-Tuned LLMs with A Single Instance

Jiawen Zhang, Lipeng He, Kejia Chen +4

Fine-tuning safety-aligned large language models (LLMs) can substantially compromise their safety. Previous approaches require many safety samples or calibration sets, which not on…

cs.CR2025

Efficient Input-level Backdoor Defense on Text-to-Image Synthesis via Neuron Activation Variation

Shengfang Zhai, Jiajun Li, Yue Liu +7

In recent years, text-to-image (T2I) diffusion models have gained significant attention for their ability to generate high quality images reflecting text prompts. However, their gr…

cs.CV2025

Sparse Autoencoder as a Zero-Shot Classifier for Concept Erasing in Text-to-Image Diffusion Models

Zhihua Tian, Sirun Nan, Ming Xu +5

Text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images but also raise people's concerns about generating harmful or misleading con…