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cs.CL2026

CoTranslator: Reverse to Forward Chain-of-Thought Translator for Reasoning Distillation

Zinan Tang, Zhuoshi Pan, Kairui Chen +5

Reasoning distillation requires chain-of-thought (CoT) data with correct answers, but obtaining such data efficiently remains challenging. Forward CoT generation (FCG) followed by…

cs.CL2026

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale

Ang Li, Ben Liu, Bin Han +215

Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…

cs.CL2026

Improving Cross-Format Robustness in Language Models with Multi-Format Training

June M. Liu, Shaomian Zheng, He Cao +3

Large language models often remain sensitive to answer format: a question solved correctly in one form may fail in another semantically equivalent form. To study this gap, we defin…

cs.CL2025

Every Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model

Ling Team, Anqi Shen, Baihui Li +101

We present Ring-1T, the first open-source, state-of-the-art thinking model with a trillion-scale parameter. It features 1 trillion total parameters and activates approximately 50 b…

cs.CL2025

Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMs

Ling Team, Bin Hu, Cai Chen +43

We present Ring-lite, a Mixture-of-Experts (MoE)-based large language model optimized via reinforcement learning (RL) to achieve efficient and robust reasoning capabilities. Built…