Papers by Jiayu Tang

2 papers
A3: Android Agent Arena for Mobile GUI Agents with Essential-State Procedural Evaluation (2026.findings-acl)

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Challenge: Existing evaluation methods for mobile GUI agents rely on static frame assessments or offline static apps.
Approach: They propose an evaluation system that leverages large language models as reward models to verify task completion and process achievement.
Outcome: The proposed system addresses the limitations of traditional function based evaluation methods on online dynamic apps.
OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment Strategy (2026.acl-long)

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Challenge: Existing methods to decouple safety enforcement from harmful feature acquisition rely on perturbation directions that conflict with harmful gradients . harmful fine-tuning attacks pose a significant challenge for service providers aiming to uphold rigorous safety standards.
Approach: They propose an orthogonal and ad hoc safety alignment strategy to decouple safety enforcement from harmful feature acquisition.
Outcome: Experiments on four large language models show that OASIS reduces the Harmful Score by 60% compared to baselines while maintaining stable task utility.

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