What it is
A small frozen study that asks 100 questions per cell from four public test sets (Belebele, PAWS-X, MedQA, KorMedMCQA) in Korean and English, recording every Jev response. It is a sample check, not a benchmark.
How it uses Jev
Jev answers multiple-choice questions: it returns a probability for every option at once plus the highest-scoring option, with no reasoning text to parse. The study records those answers and compares them across languages, tasks, and against gpt-5.6-luna.
Primitives:choice
Technique worth stealing
Ask Jev the same question in both languages to isolate language effects; reorder inputs to expose answer inconsistencies.
Evidence
Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.
- Jev-centricyes0.83
- Shows a System One patternno0.20
- Handles uncertaintyno0.04
- Measuredyes0.97
- Runnableno0.09
- Worth recommendingno0.24
- Model replicano0.05
- Problem scopescore on a 0–2 scale0.94
- About Jevyes0.98
Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 20 Sept 2026.