10 papers
RP-OPSD: Reasoning-Pivot-Guided On-Policy Self-Distillation for Multilingual Reasoning Transfer
Xinye Wang, Junxiao Liu, Shujian Huang
Multilingual reasoning transfer is crucial for extending reasoning capabilities of large language models (LLMs) beyond high-resource languages. On-policy self-distillation (OPSD) a…
Efficient Multilingual Reasoning Transfer via Progressive Code-Switching
Zhijun Wang, Junxiao Liu, Hao Zhou +3
Large reasoning models (LRMs) have achieved strong reasoning capabilities in English, yet their performance degrades significantly when required to reason in other languages. A nat…
Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers
Xin Chen, Feng Jiang, Yiqian Zhang +5
Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain fundamentally limited by a \emph{blind self…
PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning
Yunzhi Shen, Hao Zhou, Xin Huang +3
Reinforcement learning (RL) has shown strong promise for LLM-based machine translation, with recent methods such as GRPO demonstrating notable gains; nevertheless, translation-orie…
ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection
Changjiang Gao, Zixian Huang, Kaichen Yang +3
Current large reasoning models (LRMs) have shown strong ability on challenging tasks after reinforcement learning (RL) based post-training. However, previous work mainly focuses on…
GRRM: Group Relative Reward Modeling for Machine Translation
Sen Yang, Shanbo Cheng, Lu Xu +2
While Group Relative Policy Optimization (GRPO) offers a powerful framework for LLM post-training, its effectiveness in open-ended domains like Machine Translation hinges on accura…