Calibrated RL makes LLMs allocate compute on the fly, cutting inference cost twelvefold
The paper introduces C3RL, an RL algorithm that jointly optimizes correctness and confidence calibration for LLMs. With better‑calibrated confidence, the CAS inference strategy reallocates compute on the fly, slashing test‑time costs up to 12× while preserving or boosting QA accuracy.