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Geguang Pu

7 accepted papers

2026

Efficient and Effective Universal Adversarial Attack against Vision-Language Pre-training Models

ICASSP 2026oral

Vision-language pre-training (VLP) models, trained on large-scale image-text pairs, have become widely used across a variety of downstream vision-and-language (V+L) tasks. This widespread adoption raises concerns about their vulnerability to adversarial attacks. Non-universal adversarial attacks, wh…

Cited by 0SourcePDFScholar
2025

Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization

ACL 2025long

Universal goal hijacking is a kind of prompt injection attack that forces LLMs to return a target malicious response for arbitrary normal user prompts. The previous methods achieve high attack performance while being too cumbersome and time-consuming. Also, they have concentrated solely on optimizat…

2025

Perception-Guided Jailbreak Against Text-to-Image Models

AAAI 2025technical

In recent years, Text-to-Image (T2I) models have garnered significant attention due to their remarkable advancements. However, security concerns have emerged due to their potential to generate inappropriate or Not-Safe-For-Work (NSFW) images. In this paper, inspired by the observation that texts wit…

Cited by 7SourcePDFScholar
2024

Architecture-Agnostic Iterative Black-Box Certified Defense Against Adversarial Patches

ICASSP 2024accepted

The adversarial patch attack aims to fool image classifiers within a bounded, contiguous region of arbitrary changes. To address this problem in a trustworthy way, the certified patch defense methods are proposed. However, the state-of-the-art certified defenses inevitably needed to access the size…

Cited by 0SourceScholar
2024

CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection

CVPR 2024poster

Co-salient object detection (CoSOD) aims to identify the common and salient (usually in the foreground) regions across a given group of images. Although achieving significant progress state-of-the-art CoSODs could be easily affected by some adversarial perturbations leading to substantial accuracy r…

Cited by 1SourcePDFScholar
2024

Personalization as a Shortcut for Few-Shot Backdoor Attack against Text-to-Image Diffusion Models

AAAI 2024technical

Although recent personalization methods have democratized high-resolution image synthesis by enabling swift concept acquisition with minimal examples and lightweight computation, they also present an exploitable avenue for highly accessible backdoor attacks. This paper investigates a critical and un…

Cited by 29SourcePDFScholar
2021

On-the-fly Synthesis for LTL over Finite Traces

AAAI 2021technical

We present a new synthesis framework based on the on-the-fly DFA construction for LTL over finite traces (LTLf ). Extant approaches rely heavily on the construction of the complete DFA w.r.t. the input LTLf formula, whose size can be doubly exponential to the size of the formula in the worst case. U…

Cited by 24SourcePDFScholar