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LLM structured output can mask fabricated data, passing schema checks

An LLM's structured output mode can mask data extraction errors by generating plausible but false values, even when the output format is valid. This occurs because models may invent data to satisfy schema requirements rather than indicating uncertainty or missing information. A common failure mode is when an LLM provides a complete, well-formatted JSON response that contains fabricated values, such as an impossible rating, which can then be ingested as fact by downstream systems. AI

IMPACT LLM outputs may appear valid but contain fabricated data, requiring robust value-level validation beyond schema checks.

RANK_REASON The article discusses a failure mode of LLMs in structured data extraction, offering analysis and advice rather than announcing a new product or research.

Read on dev.to — LLM tag →

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

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Alex Spinov ·

    Your Scraper Returned a Clean Row. It Was Wrong.

    <p>The row looked perfect. <code>rating: 7</code>. Valid JSON, right type, no nulls, no missing keys. My schema check waved it through. The page had returned HTTP 200. The selectors hadn't moved. Everything green.</p> <p>A rating of 7 on a 5-star site is impossible. The model inv…