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DRIVE framework separates reasoning and interaction skills for web agents

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called DRIVE to improve the performance of web agents. DRIVE disentangles reasoning skills, which are abstract and transferable, from interaction skills, which are page-specific and executable. This separation allows agents to better learn and adapt to new websites by recognizing reusable task logic while grounding actions to specific page elements. Experiments show DRIVE significantly outperforms skill-free baselines in task success rates across multiple domains. AI

IMPACT Enhances web agent capabilities by improving task decomposition and page element manipulation, potentially leading to more sophisticated automated web interactions.

RANK_REASON Academic paper detailing a new framework for web agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

DRIVE framework separates reasoning and interaction skills for web agents

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Academic paper detailing a new framework for web agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Xirui Liu, Sihang Zhou, Yanning Hou, Rong Zhou, Haoyuan Chen, Maolin He, Siwei Wang, Hao Chen, Jian Huang ·

    DRIVE: Modeling Skills at the Reasoning and Interaction Levels for Web Agents under Continual Learning

    arXiv:2605.23939v1 Announce Type: new Abstract: Web agents require both high-level reasoning (for task decomposition) and low-level interactions (for page elements manipulation) to conduct different tasks. However, these knowledge types differ fundamentally: reasoning knowledge (…

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