PACE: Publisher-Adaptive Content Extraction via Agentic Automation
Web content extraction is essential for reliable LLM data pipelines, yet existing methods often struggle to jointly satisfy accuracy, scalability, and adaptability. General-purpose extractors can be applied broadly, but they are often brittle on publisher-specific layouts and richer extraction targets such as metadata, images, and tables. Direct LLM-based extraction offers greater flexibility, but incurs substantial cost and latency at scale, while manually engineered publisher-specific parsers can achieve high accuracy but require substantial human effort to build and maintain. We introduce PACE, an agentic framework for learning publisher-specific extraction configurations from represen...
| Authors | Zhanlin Liu, Munirathnam Srikanth |
|---|---|
| Primary category | cs.CL |
| Published | 20 July 2026 |
| Last updated at source | 20 July 2026 |
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