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Evidence record 5499 · automatically gathered

The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality

Automatic systems are increasingly used to assess the originality of responses in creative tasks. They offer a potential solution to key limitations of human assessment (cost, fatigue, and subjectivity), but there is preliminary evidence of a self-preference bias. Accordingly, automatic systems tend to prefer outcomes that are more closely related to their style, rather than to the human one. In this paper, we investigated how Large Language Models (LLMs) align with human raters in assessing the

Record details

Published: 22 April 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Finance, VC & PE
Retrieved: 14 July 2026

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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: Bias & fairness · Shared topic: Finance, VC & PE

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How to cite this record

ethics.ai (22 April 2026), “The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality,” evidence record 5499, https://ethics.ai/record/5499 (originally published by arXiv).

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