4 citations · 8 across the 16 of their papers we have counts for
5 papers · 1 filter
Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
Zhenyu Hou, Yujiang Li, Jie Tang +1
Reinforcement learning (RL) is becoming increasingly important for post-training large language models (LLMs). Previous RL pipelines for LLMs were mostly synchronous and batch-inte…
CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents
Yujiang Li, Zhenyu Hou, Yi Jing +2
Long-horizon agentic LLMs are increasingly limited by finite context windows, as extended interaction trajectories can exceed the maximum context length before a task is completed.…
GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, :, Aohan Zeng +184
We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…
TreeRL: LLM Reinforcement Learning with On-Policy Tree Search
Zhenyu Hou, Ziniu Hu, Yujiang Li +3
Reinforcement learning (RL) with tree search has demonstrated superior performance in traditional reasoning tasks. Compared to conventional independent chain sampling strategies wi…
T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
Zhenyu Hou, Xin Lv, Rui Lu +6
Large language models (LLMs) have demonstrated remarkable capabilities in complex reasoning tasks. However, existing approaches mainly rely on imitation learning and struggle to ac…