ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments
The model family shows gains in held-out scientific-code repair and across selected general-purpose benchmarks in code, reasoning, and knowledge, providing evidence of positive transfer from scientific experience to broader capabilities.
He-Jia Geng, Ze-Sen Huang, Hao-Yang Li et al.
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