Papers by Manman Zhang

2 papers
EVA: Evolving Semantic Adversaries for Red-Teaming GUI Agents Against Environmental Injection Attacks (2026.findings-acl)

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Challenge: Existing methods for red-teaming face a trade-off between requiring target-specific knowledge and incurring prohibitive computational costs.
Approach: They propose a framework that evolves payloads exclusively on the semantic dimension via a discovery-deployment pipeline.
Outcome: Experiments show that EVA outperforms baselines in terms of attack success rate while evolving benign seeds into successful attacks within 1.18 to 1.71 iterations.
Beyond Surface Features: Advancing Medical Vision-Language Alignment via Dynamic Evidence-Guided Preference Optimization (2026.acl-long)

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Challenge: Existing preference-based methods for medical large vision-Language Models face limitations in medical settings . existing methods are limited by overfitting to superficial cues and pseudo convergence of the preference signal.
Approach: They propose a framework that enables evidence-aware and adaptive preference learning for Med-LVLMs.
Outcome: The proposed framework improves evidence-aware and adaptive preference learning for Med-LVLMs.

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