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Home/Authors/Hanqing Guo

Hanqing Guo

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

Crypto×3Sound×1AI×1ML×1

Frequent co-authors

Xiangtao Meng2×
Wenyu Chen2×
Chuanchao Zang2×
Xinyu Gao2×
Jianing Wang2×
Li Wang2×

Research Timeline

2026
Not All Tokens Are Created Equal: Query-Efficient Jailbreak Fuzzing for LLMs

The paper proposes TriageFuzz, a token-aware fuzzing framework that significantly reduces the number of queries needed to jailbreak LLMs while maintaining high attack success rates.

Defenses at Odds: Measuring and Explaining Defense Conflicts in Large Language Models

This paper systematically measures and explains how sequential model defenses can conflict, finding that 38.9% of ordered defense sequences cause measurable risk exacerbation due to anti-aligned parameter updates in shared layers.

Audio Pirates: Black-box Audio Watermark Removal via Diffusion Priors

The paper introduces DiffErase, a black-box attack that effectively removes inaudible audio watermarks while preserving perceptual quality by utilizing diffusion models.

Highlighted terms show continued research focus across papers

Papers

cs.CRcs.SDRecentMay 28, 2026

Audio Pirates: Black-box Audio Watermark Removal via Diffusion Priors

Lingfeng Yao, Xincong Zhong, Chenpei Huang, Xuandong Zhao +5 more

The paper introduces DiffErase, a black-box attack that effectively removes inaudible audio watermarks while preserving perceptual quality by utilizing diffusion models.

View →
cs.CRRecentMay 14, 2026

Defenses at Odds: Measuring and Explaining Defense Conflicts in Large Language Models

Xiangtao Meng, Wenyu Chen, Chuanchao Zang, Xinyu Gao +4 more

This paper systematically measures and explains how sequential model defenses can conflict, finding that 38.9% of ordered defense sequences cause measurable risk exacerbation due to anti-aligned param…

View →
cs.CRcs.AIcs.LGRecentMar 24, 2026

Not All Tokens Are Created Equal: Query-Efficient Jailbreak Fuzzing for LLMs

Wenyu Chen, Xiangtao Meng, Chuanchao Zang, Li Wang +5 more

The paper proposes TriageFuzz, a token-aware fuzzing framework that significantly reduces the number of queries needed to jailbreak LLMs while maintaining high attack success rates.

View →