Position-aware trust regions in PPO improve LLM reasoning training

Uniform per-token KL thresholds in PPO-style RLVR ignore autoregressive compounding: early-token deviations cause sequence-level drift while late tokens are over-constrained. The proposed method applies position-dependent trust regions that account for cumulative prefix drift, improving training stability and reasoning performance.