Showing cs.AIShow all
3 papers · 1 filter
cs.AI2026
Apodex 1.1: Scaling Agentic Intelligence for Complex Work
B. An, B. Li, B. Wang +72
General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information sources, and executable code, toge…
cs.AI2026
OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models
Qiushi Sun, Kanzhi Cheng, Yian Wang +20
Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Verifying whether it fulfilled the…
cs.AI2026
OS-Themis: A Scalable Critic Framework for Generalist GUI Rewards
Zehao Li, Zhenyu Wu, Yibo Zhao +11
Reinforcement Learning (RL) has the potential to improve the robustness of GUI agents in stochastic environments, yet training is highly sensitive to the quality of the reward func…