activity
20242026
collaborators

13 papers

cs.CV2026

QualiRAG: Retrieval-Augmented Generation for Visual Quality Understanding

Linhan Cao, Wei Sun, Weixia Zhang +6

Visual quality assessment (VQA) is increasingly shifting from scalar score prediction toward interpretable quality understanding -- a paradigm that demands \textit{fine-grained spa…

cs.CV2025

Adapter Shield: A Unified Framework with Built-in Authentication for Preventing Unauthorized Zero-Shot Image-to-Image Generation

Jun Jia, Hongyi Miao, Yingjie Zhou +8

With the rapid progress in diffusion models, image synthesis has advanced to the stage of zero-shot image-to-image generation, where high-fidelity replication of facial identities…

eess.IV2025

DLADiff: A Dual-Layer Defense Framework against Fine-Tuning and Zero-Shot Customization of Diffusion Models

Jun Jia, Hongyi Miao, Yingjie Zhou +8

With the rapid advancement of diffusion models, a variety of fine-tuning methods have been developed, enabling high-fidelity image generation with high similarity to the target con…

cs.CV2025

VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models: Methods and Results

Hanwei Zhu, Haoning Wu, Zicheng Zhang +26

This paper presents a summary of the VQualA 2025 Challenge on Visual Quality Comparison for Large Multimodal Models (LMMs), hosted as part of the ICCV 2025 Workshop on Visual Quali…

cs.CV2025

VQualA 2025 Challenge on Face Image Quality Assessment: Methods and Results

Sizhuo Ma, Wei-Ting Chen, Qiang Gao +56

Face images play a crucial role in numerous applications; however, real-world conditions frequently introduce degradations such as noise, blur, and compression artifacts, affecting…

cs.CL2025

Sycophancy under Pressure: Evaluating and Mitigating Sycophantic Bias via Adversarial Dialogues in Scientific QA

Kaiwei Zhang, Qi Jia, Zijian Chen +5

Large language models (LLMs), while increasingly used in domains requiring factual rigor, often display a troubling behavior: sycophancy, the tendency to align with user beliefs re…