Author

Chenghao Zhang

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Preprint Aug 2026

Training Needs Trustworthy Worlds: Verified Synthetic Web Environments for Agent Learning

These results show that verified synthetic environments can serve as a scalable and reliable training substrate for compact web agents, shifting synthetic webagent learning from surface-level plausibility toward executable, state-grounded supervision.

Chenghao Zhang, Canran Xiao, Saisai Hu et al. · 0 citations

Preprint Aug 2026

From Solver Feedback to Faithful Plans: Multi-Role Reinforcement Learning for Symbolic Planning

Results show that organizing solver feedback into generation, verification, and repair roles enables more scalable and faithful annotation-free symbolic planning.

Chenghao Zhang, Yikai Mao, Shan Liu et al. · 0 citations