arXiv (All)
open access
ReScraper: Unified Scraping and Cleaning of Web Data for Effective LLM Pretraining
LLM pretraining corpora are normally cleaned by a stack of hand-written heuristics. A heuristic scraper extracts the main content from HTML, and dozens of rule-based filters then clean it, so corpus quality is capped by the coarseness and accuracy of the rules. In this work, we propose ReScraper, a
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- openbmb/Ultra-FineWeb-L1#786827
- Identifying AI Web Scrapers Using Canary Tokens#926977
- HuggingFaceFW/fineweb#786494
- DataEvolver: Automatic Data Preparation for Large Language Models through Multi-Level Self-Evolving#266259
- Adaptive Test-Time Inference for Text2Cypher with Trace Budgeting and Selective Refinement#924219
Record · ID 1119360
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive