3 papers
cs.AI2026
CARE: Contrastive Anchor-based Rubric Evolution for Large Language Model Post-Training
Siyuan Li, Xinxin Song, Chen Ruinian +5
Rubric-based reinforcement learning decomposes open-ended instructions into prompt-specific, flexible rubrics, making it better suited than reinforcement learning with verifiable r…
cs.CL2025
Higher Satisfaction, Lower Cost: A Technical Report on How LLMs Revolutionize Meituan's Intelligent Interaction Systems
Xuxin Cheng, Ke Zeng, Zhiquan Cao +65
Enhancing customer experience is essential for business success, particularly as service demands grow in scale and complexity. Generative artificial intelligence and Large Language…
cs.LG2025
Enhancing Efficiency and Exploration in Reinforcement Learning for LLMs
Mengqi Liao, Xiangyu Xi, Ruinian Chen +5
Reasoning large language models (LLMs) excel in complex tasks, which has drawn significant attention to reinforcement learning (RL) for LLMs. However, existing approaches allocate…