Papers by Hye-young Paik

    1 papers
    HiSA: Hierarchical State Abstraction for Scalable GUI Agents (2026.findings-acl)

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    Challenge: Recent multimodal large language models (MLLMs) exploit insufficient state abstraction to automate workflows.
    Approach: They propose a hierarchical state abstraction approach that actively restructures knowledge rather than passively retaining historical information.
    Outcome: The proposed approach achieves a 40.58% success rate while reducing token consumption by 69.85% and monetary costs by 55.10% compared to the best-performing baseline.

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