CalibratedDecisions.

Repo · Benchmarks & research

Jev-MedQA

Jev-style medical QA implementation on Qwen3.5-4B that selects an answer from candidates in one forward pass instead of generating text.

Open github.com ↗

How builders describe it

Jev-style medical QA implementation on Qwen3.5-4B that selects an answer from candidates in one forward pass instead of generating text. It reports 69.42% accuracy versus 67.41% for standard generation and a 10.37x speedup across 153,889 questions from nine benchmark sets.

The decision Jev makes

Benchmark questions with known answers, to check accuracy and confidence.

Where it fits

Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →

Related projects