Author

Honghao Liu

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Preprint Aug 2026

Envs-FORGE: Frontier-Optimized Reward-Grounded Environment Synthesis for Agent RL

Envs-FORGE is presented, a prompting policy that converts verifier rewards into per-seed environment-synthesis actions and solves a per-seed mixed-integer linear program (MILP) to choose the action that conditions generation.

Xiao-Jun Wu, Ce-Hao Yang, Hong-Hao Liu et al. · 2 citations

Preprint Aug 2026

LazyTrain: Limited-resource Allocation toward Zero-waste Yield Optimization in Large Language Model Training

LazyTrain is proposed, an optimization layer over a layer-streaming executor that formulates checkpoint selection, activation placement, recomputation, and CPU-GPU-NVMe communication overlap as a mixed-integer scheduling problem, then executes the solved policy during training.

Xiao-Jun Wu, Ce-Hao Yang, Hong-Hao Liu et al. · 1 citation