Papers with WEBARENA benchmark

    1 papers
    R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory (2025.acl-long)

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    Challenge: Existing methods for web agents struggle with efficient navigation and action execution due to limited visibility and understanding of web structures.
    Approach: They propose a framework that integrates memory-enhanced navigation and reflective learning to improve web agents' performance.
    Outcome: The proposed framework shows significant improvements over existing methods, including 50% reduction in navigation errors and threefold increase in task completion rates.

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