Calibrated Surprise: An Information-Theoretic Account of Creative Quality
In the era of large language models, creative writing quality lacks a computable theoretical anchor. The dominant approaches are rubric scoring -- decomposing holistic aesthetic judgment into sub-scores -- and RLHF preference signals -- replacing quality with group votes. Both bypass the statistical structure of the text itself. This paper provides an information-theoretic foundation to fill this gap. We propose 'calibrated surprise' as the information-theoretic essence of excellent creative writing. This judgment matches reading intuition and covers its opposite. This literary judgment admits a precise mathematical formulation. Under full-dimensional constraints Y, feasible writing choic...
| Authors | Bo Zou, Chao Xu |
|---|---|
| Primary category | cs.CL |
| Published | 29 April 2026 |
| Last updated at source | 4 June 2026 |
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