mlsanityData to 14 Oct 2026

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

arXiv 2510.01832 ↗First posted 2 Oct 2025cs.CLcited by 0

On the map: Deep reinforcement learning methods → RL training of language and agent models

Abstract (arXiv)

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 (SCRIpt-Based Semi-Structured Content Extraction at Web-Scale), 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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RL training of language and agent models, one of 15 directions in Deep reinforcement learning methods. Builds on 31 of its 51 references that are in the map. First posted on arXiv 2 Oct 2025.

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31 of 51 references.

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  1. 2025TTRL: Test-Time Reinforcement Learning22 Apr

Other references · 30

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  4. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,148
  5. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  6. 2024Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Researchcited by 483
  7. 2021TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Financecited by 408
  8. 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 281
  9. 2020HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Datacited by 264
  10. 2025Learning to Reason without External Rewardscited by 210
  11. 2025Spurious Rewards: Rethinking Training Signals in RLVRcited by 209
  12. 2020Open Question Answering over Tables and Textcited by 163
18 more
  1. 2025olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Modelscited by 125
  2. 2025Maximizing Confidence Alone Improves Reasoningcited by 100
  3. 2024Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Constructioncited by 70
  4. 2020UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answeringcited by 61
  5. 2023Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractorscited by 45
  6. 2024HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systemscited by 37
  7. 2021Open Domain Question Answering with A Unified Knowledge Interfacecited by 32
  8. 2020ZeroShotCeres: Zero-Shot Relation Extraction from Semi-Structured Webpagescited by 30
  9. 2024SPINACH: SPARQL-Based Information Navigation for Challenging Real-World Questionscited by 27
  10. 2022Conversational Question Answering on Heterogeneous Sourcescited by 26
  11. 2025AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corporacited by 23
  12. 2023UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Predictioncited by 20
  13. 2023AutoKG: Efficient Automated Knowledge Graph Generation for Language Modelscited by 17
  14. 2025ReaderLM-v2: Small Language Model for HTML to Markdown and JSONcited by 15
  15. 2023SUQL: Conversational Search over Structured and Unstructured Data with Large Language Modelscited by 13
  16. 2018CERES: Distantly Supervised Relation Extraction from the Semi-Structured Webcited by 11
  17. 2024SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsingcited by 11
  18. 2025Knowledge Extraction on Semi-Structured Content: Does It Remain Relevant for Question Answering in the Era of LLMs?cited by 1

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