ScribeAgent: Towards Specialized Web Agents Using Production-Scale Workflow Data

Understand

Large Language Model (LLM) agents are rapidly improving to handle increasingly complex web-based tasks.

• Most of these agents rely on general-purpose, proprietary models like GPT-4 and focus on designing better prompts to improve their planning abilities.
• However, general-purpose LLMs are not specifically trained to understand specialized web contexts such as HTML, and they often struggle with long-horizon planning.
• We explore an alternative approach that fine-tunes open-source LLMs using production-scale workflow data collected from over 250 domains corresponding to 6 billion tokens.