SOURCE-LINKED INTELLIGENCE

The Complexity Kink: A Prompt-Side Structural Complexity Index for Code-Generation Reliability

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Complexity measured from generated code is failure-dependent: a difficult prompt can yield a short failing program and be assigned low output complexity. We introduce a six-dimension prompt-side structural-complexity index scored before generation and kept separate from correctness. We select 5,000 Python prompts across six bands of a preliminary single-rater rubric. Four out-of-panel LLM raters rescore the locked prompts, giving 19,997 score rows; composite inter-rater reliability is ICC = 0.872 on the 4,998 prompts with all four ratings. We evaluate 21 models per prompt, yielding 105,000 gen

Read original source ↗ Open in workspace

recordType: paper
region: Global

Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-09-17T03:07:39.000Z

First collected: 2026-09-19T20:28:21.856Z. This is not the publication date.