arXiv cs.AI· Vagner Figueredo de Santana, Diogo Cortiz·· 6 天前AI 评分27
面向 Agentic Web 技术栈的基线评估：MASTIF 框架与 300 项 Mind2Web 任务测试
A Baseline Assessment for the Agentic Web Technology Stack
AI 导读
研究者提出 MASTIF（Multi-Agent System TestIng Framework），对 3 个 LLM、3 种协议和 4 个智能体实现框架在 300 项 Mind2Web 基准任务上进行 Agentic Web 技术栈基线评估。结果显示，选择任务专属技术栈可提升任务完成率、效率分数和社会价值稳定性分数，并减少冗长度与任务完成时间。
正文 · 原文
Abstract:The fast pace in which protocols, frameworks, and technologies are being proposed for LLM-based agents results in a complex scenario for anyone aiming to create state-of-the-art AI solutions. Without an assessment on how different protocols, frameworks, and libraries work together to compose an Agentic Web solution, developers and organizations face different challenges (e.g., skilling, governance, infrastructure) even before becoming part of the Agentic Web ecosystem. In this context, we propose a system for performing Agentic Web evaluations called MASTIF (Multi-Agent System TestIng Framework) and present a baseline assessment of Agentic Web technologies, including 3 LLMs, 3 protocols, and 4 agent implementation frameworks, against 300 Mind2Web benchmark tasks. Results suggest that selecting a task-specific technology stack may result in gains of task completion rate, efficiency score, and social value stability scores; and reductions in verbosity and time to complete tasks. With the presented results, we expect to present a baseline in terms of metrics and results for this complex and fast evolving scenario for those aiming at designing, assessing, and developing multi-agent systems.
| Subjects: | Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET); Software Engineering (cs.SE) |
| Cite as: | arXiv:2610.13703 [cs.AI] |
| (or arXiv:2610.13703v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.13703 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Vagner Figueredo De Santana [view email]
[v1]
Fri, 9 Oct 2026 14:59:24 UTC (1,950 KB)
来源：arXiv cs.AI · arxiv.org