Author

Yangtian Zi

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#natural language process... Sep 2025

AgentPack: A Dataset of Code Changes, Co-Authored by Agents and Humans

It is shown that models fine-tuned on AgentPack can outperform models trained on prior human-only commit corpora, highlighting the potential of using public data from software engineering agents to train future code-editing models.

Yang-Tian Zi, Zi-Xuan Wu, Aleksander Boruch-Gruszecki et al. · arXiv.org · 7 citations · ⚡2

#machine learning Aug 2025

Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning Environment

Agnostics introduces Agnostics, a language-agnostic post-training pipeline that eliminates per-language engineering, and releases the language-agnostic training datasets, making RL post-training in any programming language as simple as editing a short YAML file.

Aleksander Boruch-Gruszecki, Yangtian Zi, Zi-Xuan Wu et al. · arXiv.org · 5 citations