57 citations · 66 across the 16 of their papers we have counts for
4 papers · 1 filter
MCP-Universe RL: A Framework for Training MCP Tool-Use Agents via Reinforcement Learning
Ziyang Luo, Yan Yang, Xiangru Jian +5
Reinforcement learning (RL) has become an effective way to improve the tool-use ability of large language models (LLMs), but most existing RL frameworks stop at the policy update.…
StateAct: Program State, before Pixels, for Long-Horizon Computer-Use Agents
Yan Yang, Xiangru Jian, Ziyang Luo +7
Computer-use agents are usually improved by strengthening perception: better models for reading a screenshot and choosing where to click. Yet a screenshot is only a lossy rendering…
Chain of Modality: From Static Fusion to Dynamic Orchestration in Omni-MLLMs
Ziyang Luo, Nian Liu, Junwei Han
Omni-modal Large Language Models (Omni-MLLMs) promise a unified integration of diverse sensory streams. However, recent evaluations reveal a critical performance paradox: unimodal…
GPA: Learning GUI Process Automation from Demonstrations
Zirui Zhao, Jun Hao Liew, Yan Yang +5
GUI Process Automation (GPA) is a lightweight but general vision-based Robotic Process Automation (RPA), which enables fast and stable process replay with only a single demo. Addre…