Unit-test-based evaluation shows consistently negative correlations with human judgment, disproportionately penalizing complex high-quality interactive designs¶
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Evidence · 1 study · designr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
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q2 i? The unit test baseline correlates negatively with human ratings across all dimensions (interactivity r = −0.600), suggesting brittle test scripts penalize complex but high-quality interactive designs. → Xiaozao Wang 2026
Evidence¶
Xiaozao Wang 2026¶
Xiaozao Wang, Zhewei Wang, Hongyi Wen. (2026). Evaluating Interactivity: Toward Automated Assessment of AI-Generated Explorable Explanations. https://arxiv.org/abs/2606.31012 doi:10.48550/arxiv.2606.31012
q2 · i? · design · r2
Authors' interpretation of the balanced-dataset results in the paper, where the unit test baseline using LLM-generated Playwright tests showed negative correlations with human judgments on all four dimensions, including r = −0.600 on interactivity per Table 1.
"Unit testing shows consistently negative correlations, suggesting that brittle test scripts disproportionately penalize complex but high-quality interactive designs."
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Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
unit-test-negative-correlation-human-judgment |
title |
Unit-test-based evaluation shows consistently negative correlations with human judgment, disproportionately penalizing complex high-quality interactive designs |
description |
Unit-test-based evaluation shows consistently negative correlations with human judgment, disproportionately penalizing complex high-quality interactive designs |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — xiaozao-wang-2026 |
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