PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning

In three linesPEGRL is a two-stage RL framework for LLM-based machine translation. It uses post-editing as an auxiliary task to stabilize training and guide optimization. Tests on EN→FI, EN→TR, EN↔ZH show consistent gains; EN→TR achieves performance comparable to DeepSeek-V3.2 on COMET-KIWI.

Summary generated by Claude — human-verified