Author

Jie Jiang

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#machine learning Preprint Sep 2026

What Should Data Teach? Moving Bottlenecks Across Circuit, Store, and Use

What should data teach a language model at a particular point in training? A circuit view reveals three distinct bottlenecks: forming a computation, making its required content available, and selecting among available routes. A shared diagnosis-to-data principle connects them: localize the missing operation, preserve i...

Yi-Xiao Chen, Ke Cheng, Jiang-Tao Guan et al. · 0 citations

#machine learning Preprint Sep 2026

The Token Before the Value Is the Key: How Hybrid Architectures Organize Induction Circuits

Hybrid language models can improve capability as well as efficiency, raising the question of how architectural complementarity becomes learned computation. We examine the established induction roles of Carrying predecessor information, Matching a source by content, and Copying its value. How are these position-sensitiv...

Ke Cheng, Xin Xu, Yi-Xiao Chen et al. · 0 citations