Researchers have developed SCRIBES, a reinforcement learning framework designed to extract structured information from semi-structured web content like HTML tables and lists. This method generates reusable extraction scripts by leveraging layout similarity across webpages within the same site as a reward signal, thus avoiding resource-intensive per-page LLM inference. The framework improves by training on synthetic annotations from CommonCrawl data, outperforming existing methods in script quality and enhancing downstream question answering accuracy for models like GPT-4o. AI
IMPACT Enables more efficient and scalable extraction of structured data from the web, potentially improving downstream AI applications.
RANK_REASON The cluster describes a new research paper detailing a novel framework for data extraction. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- Common Crawl
- DagsHub
- Gotit.pub
- GPT-4o
- Hugging Face
- ScienceCast
- Shicheng Liu
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