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#artificial intelligence Preprint Oct 2026

Scalable Minimal-Change Learning for Controllable Image Editing

Image editing should change only the attributes specified by an instruction while preserving everything else, yet current methods often make unintended changes. We treat this minimal-change principle as an optimization objective for instruction-based editing. Latent L1 regularization is a poor proxy for output locality...

Shuo Chen, Feng-Ming Huang, Yu Yao et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Recursive Improvement of a Differentiable Scientific Software Ecosystem

Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a heterogeneous software ecosystem requires specialized effort to implement derivatives, integrate interfaces and evaluate quality. AI coding agents can accelerate this tran...

Peng-Cheng Hou, Xiao-Jun Tan, Si-Han Hu et al. · 0 citations

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