6 papers
Tree Training: Accelerating Agentic LLMs Training via Shared Prefix Reuse
Jinghui Wang, Shaojie Wang, Yinghan Cui +9
Agentic large language model (LLM) training often involves multi-turn interaction trajectories that branch into multiple execution paths due to concurrent tool use, think-mode, sub…
KAT-Coder-V2 Technical Report
Fengxiang Li, Han Zhang, Haoyang Huang +43
We present KAT-Coder-V2, an agentic coding model developed by the KwaiKAT team at Kuaishou. KAT-Coder-V2 adopts a "Specialize-then-Unify" paradigm that decomposes agentic coding in…
KAT-Coder Technical Report
Zizheng Zhan, Ken Deng, Jinghui Wang +37
Recent advances in large language models (LLMs) have enabled progress in agentic coding, where models autonomously reason, plan, and act within interactive software development wor…
SeamlessFlow: A Trainer Agent Isolation RL Framework Achieving Bubble-Free Pipelines via Tag Scheduling
Jinghui Wang, Shaojie Wang, Yinghan Cui +24
We introduce SeamlessFlow, a server based reinforcement learning (RL) framework that addresses two core challenges in industrial scale RL: (1) decoupling RL training from the compl…
KAT-V1: Kwai-AutoThink Technical Report
Zizheng Zhan, Ken Deng, Huaixi Tang +27
We present Kwaipilot-AutoThink (KAT), an open-source 40B large language model developed to address the overthinking problem in reasoning-intensive tasks, where an automatic thinkin…
SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM
Xiaojiang Zhang, Jinghui Wang, Zifei Cheng +14
Recent advances of reasoning models, exemplified by OpenAI's o1 and DeepSeek's R1, highlight the significant potential of Reinforcement Learning (RL) to enhance the reasoning capab…