@inproceedings{luo-etal-2025-browsing,
    title = "Browsing Like Human: A Multimodal Web Agent with Experiential Fast-and-Slow Thinking",
    author = "Luo, Haohao  and
      Kuang, Jiayi  and
      Liu, Wei  and
      Shen, Ying  and
      Luan, Jian  and
      Deng, Yang",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.697/",
    pages = "14232--14251",
    ISBN = "979-8-89176-251-0",
    abstract = "Automating web navigation which aims to build a web agent that follows user instructions to complete tasks like booking flights by interacting with websites, has received increasing attention due to its practical value. Although existing web agents are mostly equipped with visual perception, planning, and memory abilities, their reasoning process are still deviate from human cognition. In this work, we study the human thought pattern to empower agent with more human-like abilities in web navigation. To tackle this problem, we propose a novel multimodal web agent framework called WebExperT, which is designed to emulate the human planning process of ``thinking fast and slow'' to effectively decompose complex user instructions. Furthermore, WebExperT leverages experiential learning by reflecting from failure for continuously refining planning and decision-making outcomes. Experimental results on the Mind2Web benchmark demonstrate the superiority of WebExperT in both supervised and unsupervised settings."
}