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Evidence record 6207 · automatically gathered

Beyond Surface Judgments: Human-Grounded Risk Evaluation of LLM-Generated Disinformation

Large language models (LLMs) can generate persuasive narratives at scale, raising concerns about their potential use in disinformation campaigns. Assessing this risk ultimately requires understanding how readers receive such content. In practice, however, LLM judges are increasingly used as a low-cost substitute for direct human evaluation, even though whether they faithfully track reader responses remains unclear. We recast evaluation in this setting as a proxy-validity problem and audit LLM ju

Record details

Published: 8 April 2026
Source: arXiv
Category: Research
Topics: Misinformation · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Misinformation · Shared topic: Transparency

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How to cite this record

ethics.ai (8 April 2026), “Beyond Surface Judgments: Human-Grounded Risk Evaluation of LLM-Generated Disinformation,” evidence record 6207, https://ethics.ai/record/6207 (originally published by arXiv).

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