arXiv:2608.30005v1 Announce Type: new
Abstract: Rubric-based reinforcement learning extends RL beyond tasks with exact answers or rule-based verifiers by scoring responses against instance-specific c...
By Fengyu Xie, Yilun Zhao, Bingsen Chen, Arman Cohan, Chen Zhao
The paper introduces a two‑stage training framework for rubric‑based reinforcement learning (RL) that first uses rubric‑privileged on‑policy distillation (RP‑OPD) to provide dense token‑level supervision, then applies RL to optimize the rubric reward. In RP‑OPD, a student model learns to match a rubric‑aware teacher’s next‑token distributions on student‑generated prefixes. Experiments on HealthBench, ResearchQA, and RubricHub Science show that this two‑stage approach yields the highest scores and reduces reward hacking compared to a standard SFT + RL baseline.
By Xinpeng Wang, Wei Shi, Yu-Chia Chen, Maria Zontak, Yun He, Richard Yuanzhe Pang
Post-training of reasoning language models is commonly driven by supervised distillation and reinforcement learning with verifiable rewards. Distillation often relies on chain-of-thought annotations that are expensive to obtain and may themselves be noisy, incomplete, or partially incorrect; even when the final solution is correct, an imperfect rationale can interfere with learning.
LLM-as-judge is essential for evaluating open-ended text and steering post-training, yet improving the judge itself typically relies on expensive annotations, reward models, or distillation from stron...
Large language models (LLMs) have been widely applied to automated essay scoring (AES) and automated feedback generation (AFG). However, existing studies rely primarily on prompt engineering or supervised fine-tuning, while systematic research on reinforcement learning (RL) post-training and automated evaluation of feedback quality remains limited.
arXiv:2606. 19327v1 Announce Type: new Abstract: Post-training of reasoning language models is commonly driven by supervised distillation and reinforcement learning with verifiable rewards.
By Siyi Gu, Jialin Chen, Sophia Zhou, Arman Cohan, Rex Ying