Author

Manish Prajapat

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#machine learning Preprint Oct 2026

ANTE: Anticipate, Then Execute -- Learning Internal World Models for Coding Agents from Verified Beliefs

Rapid advances in large language models have made software engineering agents capable of tackling complex coding tasks. Within a containerized environment, a coding agent receives tool responses or execution results, and determines its later actions by those earlier results. However, most existing coding agents never l...

Yi-Rou Ge, Kang-Rui Ruan, Ji-Fan Chen et al. · 0 citations

#machine learning Preprint Oct 2026

Reward-Aligned Distillation

Reinforcement learning with verifiable rewards improves the reasoning capabilities of large language models, but remains computationally expensive and sample inefficient. On-policy distillation (OPD) provides dense token-level supervision from a stronger teacher, yet standard OPD distills every token regardless of whet...

Yilan Chen, Zian Su, Manish Prajapat et al. · 0 citations