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

Reward-Aligned Distillation (RAD), a bilevel framework that weights distillation signals based on their predicted effect on the student's post-update reward, supports reward-guided weighting of teacher supervision across model families and tasks.

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