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20232026
most citedYour Large Language Model is Secretly a Fairness Proponent and You Should Prompt it Like One

3 citations · 8 across the 13 of their papers we have counts for

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14 papers · 1 filter

cs.CV2026

Verify Claimed Text-to-Image Models via Boundary-Aware Prompt Optimization

Zidong Zhao, Yihao Huang, Qing Guo +5

As Text-to-Image (T2I) generation becomes widespread, third-party platforms increasingly integrate multiple model APIs for convenient image creation. However, false claims of using…

cs.CV2025

Beyond Pixels: Semantic-aware Typographic Attack for Geo-Privacy Protection

Jiayi Zhu, Yihao Huang, Yue Cao +5

Large Visual Language Models (LVLMs) now pose a serious yet overlooked privacy threat, as they can infer a social media user's geolocation directly from shared images, leading to u…

cs.CV2025

Scale-Invariant Adversarial Attack against Arbitrary-scale Super-resolution

Yihao Huang, Xin Luo, Qing Guo +5

The advent of local continuous image function (LIIF) has garnered significant attention for arbitrary-scale super-resolution (SR) techniques. However, while the vulnerabilities of…

cs.CV2024

Concept Guided Co-salient Object Detection

Jiayi Zhu, Qing Guo, Felix Juefei-Xu +3

Co-salient object detection (Co-SOD) aims to identify common salient objects across a group of related images. While recent methods have made notable progress, they typically rely…

cs.CV20241 cited

Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack

Xiaojun Jia, Sensen Gao, Qing Guo +6

Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of tra…

cs.CV20241 cited

HTS-Attack: Heuristic Token Search for Jailbreaking Text-to-Image Models

Sensen Gao, Xiaojun Jia, Yihao Huang +5

Text-to-Image(T2I) models have achieved remarkable success in image generation and editing, yet these models still have many potential issues, particularly in generating inappropri…