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Jun Liu

4 papers hereh-index 216 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.CR1
same name
  • Jun Liu — 14 papers, h 5
  • Jun Liu — 13 papers, h 7
  • Jun Liu — 12 papers, h 8
  • Jun Liu — 12 papers, h 8
  • Jun Liu — 9 papers, h 3
  • Jun Liu — 9 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.CV2026

EvoGuard: An Extensible Agentic RL-based Framework for Practical and Evolving AI-Generated Image Detection

Chenyang Zhu, Maorong Wang, Jun Liu +2

The rapid proliferation of AI-Generated Images (AIGIs) poses severe misinformation risks, making AIGI detection critical yet challenging. Traditional detection paradigms mainly rel…

cs.CV2025

Making Every Step Effective: Jailbreaking Large Vision-Language Models Through Hierarchical KV Equalization

Shuyang Hao, Yiwei Wang, Bryan Hooi +4

In the realm of large vision-language models (LVLMs), adversarial jailbreak attacks serve as a red-teaming approach to identify safety vulnerabilities of these models and their ass…

cs.CR2025

Tit-for-Tat: Safeguarding Large Vision-Language Models Against Jailbreak Attacks via Adversarial Defense

Shuyang Hao, Yiwei Wang, Bryan Hooi +5

Deploying large vision-language models (LVLMs) introduces a unique vulnerability: susceptibility to malicious attacks via visual inputs. However, existing defense methods suffer fr…

cs.CV2024

Exploring Visual Vulnerabilities via Multi-Loss Adversarial Search for Jailbreaking Vision-Language Models

Shuyang Hao, Bryan Hooi, Jun Liu +3

Despite inheriting security measures from underlying language models, Vision-Language Models (VLMs) may still be vulnerable to safety alignment issues. Through empirical analysis,…

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