ML Anthology

SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning

Shicheng Liu, Kai Sun, Lisheng Fu, Xilun Chen, Xinyuan Zhang, Zhaojiang Lin, Rulin Shao, Yue Liu, Anuj Kumar, Wen-tau Yih, Xin Luna Dong
ICLR 2026
/iclr/2026/liu2026iclr-scribes/

Abstract

Semi-structured content in HTML tables, lists, and infoboxes accounts for a substantial share of factual data on the web, yet the formatting complicates usage, and reliably extracting structured information from them remains challenging. Existing methods either lack generalization or are resource-intensive due to per-page LLM inference. In this paper, we introduce SCRIBES (**SCRI**pt-**B**ased Semi-Structured Content **E**xtraction at Web-**S**cale), a novel reinforcement learning framework that leverages layout similarity across webpages within the same site as a reward signal. Instead of processing each page individually, SCRIBES generates reusable extraction scripts that can be applied to groups of structurally similar webpages. Our approach further improves by iteratively training on synthetic annotations from in-the-wild CommonCrawl data. Experiments show that our approach outperforms strong baselines by over 13\% in script quality and boosts downstream question answering accuracy by more than 4\% for GPT-4o, enabling scalable and resource-efficient web information extraction.

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Cite

Text

Liu et al. "SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning." International Conference on Learning Representations, 2026.

Markdown

[Liu et al. "SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning." International Conference on Learning Representations, 2026.](https://mlanthology.org/iclr/2026/liu2026iclr-scribes/)

BibTeX

@inproceedings{liu2026iclr-scribes,
  title     = {{SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning}},
  author    = {Liu, Shicheng and Sun, Kai and Fu, Lisheng and Chen, Xilun and Zhang, Xinyuan and Lin, Zhaojiang and Shao, Rulin and Liu, Yue and Kumar, Anuj and Yih, Wen-tau and Dong, Xin Luna},
  booktitle = {International Conference on Learning Representations},
  year      = {2026},
  url       = {https://mlanthology.org/iclr/2026/liu2026iclr-scribes/}
}