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cs.LG2026
Trace2World: Reconstructing App Worlds from Real Interaction Traces for Scalable GUI Agent Training
Zezhou Wang, Hanzhang Zhou, Panrong Tong +5
Scaling GUI reinforcement learning requires environments that preserve real-app behavior. Yet coupling behavior inference with coding can turn partial traces into runnable mocks wi…
cs.LG2026
ProCredit: From Outcome Rewards to Progress Credit in Agentic Reinforcement Learning
Ming Ma, Yi Zhu, Yiran Zhong +7
Long-horizon agentic tasks require an agent to modify an environment through a sequence of tool calls, with success determined by the final state. The standard recipe assigns a sin…