3 papers
cs.AI2026
Shorten After You're Right: Lazy Length Penalties for Reasoning RL
Danlong Yuan, Tian Xie, Shaohan Huang +5
Large reasoning models, such as OpenAI o1 or DeepSeek R1, have demonstrated remarkable performance on reasoning tasks but often incur a long reasoning path with significant memory…
cs.LG2026
Controlled LLM Training on Spectral Sphere
Tian Xie, Haoming Luo, Haoyu Tang +9
Scaling large models requires optimization strategies that ensure rapid convergence grounded in stability. Maximal Update Parametrization (P) provides a theoretical…
cs.CL2025
Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning
Tian Xie, Zitian Gao, Qingnan Ren +7
Inspired by the success of DeepSeek-R1, we explore the potential of rule-based reinforcement learning (RL) in large reasoning models. To analyze reasoning dynamics, we use syntheti…