AICD Bench - Robust Binary Classification (Zero-Shot): leaderboard
Detection of AI-generated code from AICD Bench (Orel et al., 2026): an LLM prompted zero-shot decides whether a code sample is human-written or machine-generated, with test code from programming languages and domains unseen in training. Macro-F1 in percent on a 5% sample stratified by label, domain and language; higher is better.
Metric: Macro-F1 (%; human-written vs machine-generated code under unseen languages and domains; 5% sample stratified by label, domain and language; zero-shot prompt). Source: arxiv.org. Saturation forecast: Around February 2027. 2 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemma 3 27B | 58.45 | #1638 |
| 2 | Gemini 2.5 Flash | 57.15 | #452 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=aicd-bench-robust-binary-classification-zero-shot · How It Works · Data refreshed daily, snapshot 2026-11-12.