Reward shaping slashes reasoning steps by 65%
Tailored reinforcement‑learning rewards reactivate the dormant THINK circuitry in hybrid language models, chopping chain‑of‑thought traces by roughly two‑thirds without sacrificing answer quality. The surprise is that a modest reshaping of the reward signal does more than steer behavior—it resurrec…
Read the full story at DEV Community — Machine Learning ↗
Timeline · 1 report
- 2026-10-20 05:00 · DEV Community — Machine Learning
Reward shaping slashes reasoning steps by 65%