5 citations · 7 across the 8 of their papers we have counts for
5 papers · 1 filter
Multi-turn Training with Basic Human Feedback Helps Little on LLM Reasoning
Qiang Liu, Wuganjing Song, Zhenzhou Lin +4
The reasoning capabilities of Large Language Models (LLMs) are typically developed through the single-turn reinforcement learning, whereas real-world applications often involve mul…
TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task Execution
Mingyuan Zhong, Xia Chen, Davin Win Kyi +3
Accessibility checkers are tools in support of accessible app development, and their use is encouraged by accessibility best practices. However, most current checkers evaluate stat…
UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Haoming Wang, Haoyang Zou, Huatong Song +109
The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…
Adaptive Group Policy Optimization: Towards Stable Training and Token-Efficient Reasoning
Chen Li, Nazhou Liu, Kai Yang
Since DeepSeek-R1 popularized, Group Relative Policy Optimization (GRPO) has become the core part of training Reasoning LLMs. However, we find some deficiency that influences RL st…
UI-TARS: Pioneering Automated GUI Interaction with Native Agents
Yujia Qin, Yining Ye, Junjie Fang +32
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., keyboard and mouse operations). U…