4 papers
TAT-R1: Terminology-Aware Translation with Reinforcement Learning and Word Alignment
Zheng Li, Mao Zheng, Mingyang Song +1
Recently, deep reasoning large language models(LLMs) like DeepSeek-R1 have made significant progress in tasks such as mathematics and coding. Inspired by this, several studies have…
SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation
Wenjie Yang, Mao Zheng, Mingyang Song +2
Large language models (LLMs) have recently demonstrated remarkable capabilities in machine translation (MT). However, most advanced MT-specific LLMs heavily rely on external superv…
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM
Codefuse, Ling Team, : +30
Recent advancements in code large language models (LLMs) have demonstrated remarkable capabilities in code generation and understanding. It is still challenging to build a code LLM…
FastCuRL: Curriculum Reinforcement Learning with Stage-wise Context Scaling for Efficient Training R1-like Reasoning Models
Mingyang Song, Mao Zheng, Zheng Li +4
Improving training efficiency continues to be one of the primary challenges in large-scale Reinforcement Learning (RL). In this paper, we investigate how context length and the com…