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Guardian Crawler system enhances knowledge discovery from noisy web data

By PulseAugur Editorial · [2 sources] ·

Researchers have developed Guardian Crawler, a new retrieval-first system designed for knowledge discovery and evidence-grounded summarization from noisy web data. The system combines BM25 retrieval with advanced reranking techniques and constrained retrieval-augmented generation, incorporating explicit document citations. Experiments on a synthetic corpus showed that risk-based reranking achieved superior descriptive retrieval scores, with the best configurations reaching an NDCG@10 of 0.94. While the system demonstrated feasibility as a controlled testbed, further validation is needed for statistical superiority and faithfulness on live web data. AI

IMPACT This system could improve the reliability of information extraction and summarization from unstructured, noisy web data.

RANK_REASON The cluster contains a research paper detailing a new system and its experimental results.

Read on arXiv cs.IR (Information Retrieval) →

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

Guardian Crawler system enhances knowledge discovery from noisy web data

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Joshua Castillo, Santosh Nukavarapu, Ravi Mukkamala ·

    Guardian Crawler: Retrieval-First Knowledge Discovery with Bounded LLM Augmentation for Noisy Web Intelligence

    arXiv:2608.08994v1 Announce Type: cross Abstract: Retrieving relevant evidence from noisy web data is challenging, particularly in sensitive domains containing incomplete reports, heterogeneous language, and irrelevant content. We present Guardian Crawler, a reproducible retrieva…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Ravi Mukkamala ·

    Guardian Crawler: Retrieval-First Knowledge Discovery with Bounded LLM Augmentation for Noisy Web Intelligence

    Retrieving relevant evidence from noisy web data is challenging, particularly in sensitive domains containing incomplete reports, heterogeneous language, and irrelevant content. We present Guardian Crawler, a reproducible retrieval-first testbed for controlled experiments on know…

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