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cs.LG2025
Causality Decodability, and Vice Versa: Lessons from Interpreting Counting ViTs
Lianghuan Huang, Yingshan Chang
Mechanistic interpretability seeks to uncover how internal components of neural networks give rise to predictions. A persistent challenge, however, is disentangling two often confl…
cs.LG2025
Learning Model Successors
Yingshan Chang, Yonatan Bisk
The notion of generalization has moved away from the classical one defined in statistical learning theory towards an emphasis on out-of-domain generalization (OODG). There has been…