WebWalker: Benchmarking LLMs in Web Traversal

• URL: http://arxiv.org/abs/2501.07572v2
• Date: Tue, 14 Jan 2025 15:06:56 GMT
• Title: WebWalker: Benchmarking LLMs in Web Traversal
• Authors: Jialong Wu, Wenbiao Yin, Yong Jiang, Zhenglin Wang, Zekun Xi, Runnan Fang, Linhai Zhang, Yulan He, Deyu Zhou, Pengjun Xie, Fei Huang,
• Abstract summary: We introduce WebWalkerQA, a benchmark designed to assess the ability of LLMs to perform web traversal. We propose WebWalker, which is a multi-agent framework that mimics human-like web navigation through an explore-critic paradigm.
• Score: 64.48425443951749
• License:
• Abstract: Retrieval-augmented generation (RAG) demonstrates remarkable performance across tasks in open-domain question-answering. However, traditional search engines may retrieve shallow content, limiting the ability of LLMs to handle complex, multi-layered information. To address it, we introduce WebWalkerQA, a benchmark designed to assess the ability of LLMs to perform web traversal. It evaluates the capacity of LLMs to traverse a website's subpages to extract high-quality data systematically. We propose WebWalker, which is a multi-agent framework that mimics human-like web navigation through an explore-critic paradigm. Extensive experimental results show that WebWalkerQA is challenging and demonstrates the effectiveness of RAG combined with WebWalker, through the horizontal and vertical integration in real-world scenarios.

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