3 papers
cs.CL2025
Demystifying Reinforcement Learning in Agentic Reasoning
Zhaochen Yu, Ling Yang, Jiaru Zou +2
Recently, the emergence of agentic RL has showcased that RL could also effectively improve the agentic reasoning ability of LLMs, yet the key design principles and optimal practice…
cs.CL2025
ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates
Ling Yang, Zhaochen Yu, Bin Cui +1
We present that hierarchical LLM reasoning via scaling thought templates can effectively optimize the reasoning search space and outperform the mathematical reasoning capabilities…
cs.CL2025
SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction
Ling Yang, Zhaochen Yu, Tianjun Zhang +4
Large language models (LLMs) like GPT-4, DeepSeek-R1, and ReasonFlux have shown significant improvements in various reasoning tasks. However, smaller LLMs still struggle with compl…