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Research pipeline's structural citations fail to detect source fabrications

By PulseAugur Editorial · [1 sources] ·

A research pipeline designed to ensure trustworthy citations was evaluated and found to be vulnerable to source-borne fabrications. While the pipeline maintained 100% citation accuracy by verifying claims against their sources, it failed to detect injected false information within those sources. The system, which uses a structural approach without a language model, was susceptible to various attacks, including poisoned sources, swapped figures, and misattributed information, indicating that structural citation alone does not guarantee the truthfulness of research. AI

IMPACT Highlights the limitations of structural citation in AI research pipelines and the need for external source verification.

RANK_REASON The item describes a research paper detailing a novel evaluation pipeline for research agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Research pipeline's structural citations fail to detect source fabrications

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34 / 100
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The item describes a research paper detailing a novel evaluation pipeline for research agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Tushar Kumar ·

    Citation Is Not Truth: A Three-Metric Evaluation of an Extractive Research Pipeline

    <h1> Citation Is Not Truth: A Three-Metric Evaluation of an Extractive Research Pipeline </h1> <p><strong>Abstract.</strong> I built a research agent whose citations are structural: a researcher extracts claims from sources, a critic admits only claims whose content tokens are co…

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