---
id: 20260503-T0-02
title: "AutoSurfer：生成高质量网页轨迹数据，提升网页智能体操作准确率"
title_en: "AutoSurfer Boosts Web Agent Accuracy by Generating High-Quality Trajectory Data"
url: https://ai.daily.yangsir.net/daily/20260503-T0-02
issue_date: 2026-05-03
publish_date: 2026-05-02T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2604.27253
---

# AutoSurfer：生成高质量网页轨迹数据，提升网页智能体操作准确率

尽管多模态大模型推动了网页智能体的发展，但高质量网页轨迹训练数据的稀缺严重限制了其准确率。arXiv发表的新研究（2604.27253）提出了AutoSurfer方案，通过综合性的浏览、学习和建模过程，能够自动生成高质量的网页操作轨迹数据。这为训练更可靠的网页自动化智能体提供了必要的数据支持，开发者可借此提升智能体在复杂网站任务中的表现。

## English Version

**AutoSurfer Boosts Web Agent Accuracy by Generating High-Quality Trajectory Data**

While multimodal LLMs have advanced web agents, their accuracy is limited by the scarcity of high-quality web trajectory training data. A new paper on arXiv (2604.27253) proposes AutoSurfer, a framework that automatically generates high-quality web trajectory data through comprehensive surfing, learning, and modeling. Developers can use this to train more reliable web automation agents.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2604.27253)

**详情页**：https://ai.daily.yangsir.net/daily/20260503-T0-02

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