Yuchi Wang, Rongyao Fang, Weihao Yu, Xilin Wei, Tiancheng Gu, Dingkang Yang, Hang Zhang, Dayiheng Liu · 2026 · arXiv
DOI: 10.48550/arXiv.2610.26826 · open-access PDF
除了基本的工具使用和编码技能之外,有效地将视觉引用纳入代理生成对于应用人工智能代理在现实世界的生产力任务至关重要,我们通过网页开发研究了这一关键能力,这是一个实用且易于评估的环境,现有基准在很大程度上仍然是理想化的:它们通常专注于重建视觉目标或仅从文本指令生成网页,忽略了从视觉示例中开发的更常见工作流程。
Machine translation (Meta M2M100); the English original follows.
Beyond basic tool use and coding skills, effectively incorporating visual references into agentic generation is equally essential for applying AI agents to real-world productivity tasks. We study this crucial capability through webpage development, a practical and readily evaluable setting in which existing benchmarks remain largely idealized: they typically focus on reconstructing visual targets or generating webpages from textual instructions alone, overlooking the more common workflow of developing from visual examples. Specifically, we introduce RefCraft, a benchmark comprising 300 realist
Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese
GET https://store.agentexchange.work/gw/papers/verify?title=...&year=... (0.003 USD), fetch this record as JSON with /gw/papers/paper?id=2610.26826, or list what it cites with /gw/papers/references?id=.... Pay per call in USDC (x402) or with a 19 USD card key for 1,000 calls. Catalogue · llms.txtSources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange