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Co-Scraper framework uses Qwen3 8B for advanced web data extraction

By PulseAugur Editorial · [2 sources] ·

Researchers have developed Co-Scraper, a novel two-stage framework for efficient web data extraction. This system utilizes a fine-tuned Qwen3 8B model to integrate query-aware DOM pruning with stable extraction strategy induction. Co-Scraper demonstrates state-of-the-art performance on the SWDE dataset, achieving a 94.78% F1 score and a 90.39% reuse success rate, significantly improving the accuracy and resilience of web data acquisition. AI

IMPACT Enhances accuracy and resilience in web data acquisition tasks through advanced AI techniques.

RANK_REASON The cluster describes a research paper published on arXiv detailing a new framework for web data extraction.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Shoupeng Wang, Jiantao Qiu, Wuyang Zhang, Conghui He ·

    Co-Scraper: query-aware DOM Pruning and Reusable Scraper Synthesis for Lightweight Web Data Extraction

    arXiv:2606.14821v1 Announce Type: cross Abstract: The abundant and heterogeneous nature of web content necessitates automated information extraction, and generating scrapers that can be reused across similar web pages offers an effective solution for scalable data extraction. In …

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Conghui He ·

    Co-Scraper: query-aware DOM Pruning and Reusable Scraper Synthesis for Lightweight Web Data Extraction

    The abundant and heterogeneous nature of web content necessitates automated information extraction, and generating scrapers that can be reused across similar web pages offers an effective solution for scalable data extraction. In this work, we propose Co-Scraper, a two-stage fram…

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