collaborators

16 papers

cs.LG2026

Qwen-CUA: Native Computer Use for (almost) Everything

Dunjie Lu, Shuai Bai, Tianyi Bai +42

Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking, large-scale interactive expe…

cs.CL2026

PhoneBuddy: Training Open Models for Agentic Phone Use

Zhengyang Tang, Xin Lai, Pengyuan Lyu +23

Phones are becoming an important execution surface for general-purpose agents, but training open models for reliable phone use remains difficult because the environment that matter…

cs.CL2026

Qwen-AgentWorld: Language World Models for General Agents

Yuxin Zuo, Zikai Xiao, Li Sheng +30

A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning. In this work, we investigat…

cs.CL2026

GameCraft-Bench: Can Agents Build Playable Games End-to-End in a Real Game Engine?

Tongxu Luo, Rongsheng Wang, Jiaxi Bi +22

Game generation is an emerging application of coding agents, requiring models to transform natural-language specifications into playable interactive systems. Unlike traditional cod…

cs.AI2026

CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents

Bowen Wang, Dunjie Lu, Junli Wang +11

Reinforcement learning with verifiable rewards (RLVR) has driven breakthroughs in domains such as math, tool-use, and software engineering, yet its extension to computer-use agents…

cs.LG2026

TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network

Guangxin He, Yuan Cao, Yutong He +4

Decentralized training of large language models offers the opportunity to pool computational resources across geographically distributed participants, but is often bottlenecked by…