arXiv AI By Minseon Kim, Zhengyan Shi, Emiliano Penaloza, Christopher Cui, Roger Creus Castanyer, Maryam Hashemzadeh, Isadora White, Jonathan Light, Jeonghye Kim, Matheus Pereira, Darya Moldavskaya, Chinmay Singh, Fabio Vera, Baolin Peng, Xingdi Yuan, Marc-Alexandre C\^ot\'e, Alessandro Sordoni

FrogNano: Training a 4B Coding Agent via Online Task Synthesis

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FrogNano is a 4B coding agent trained exclusively with reinforcement learning on about 1,500 synthetic software engineering environments. Its training leverages an online task synthesis pipeline that generates tasks at the current agent’s learnability frontier, improving performance without distilling from larger models. The report details the methodology, evaluates the agent across diverse environments, and analyzes its effectiveness as a lightweight coding agent for minimal hardware.

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arXiv AI
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arXiv AI
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ProgramGym: Scaling Training Environments for Long-Horizon Program Reproduction Agents

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