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Downstream classifier accuracy can actually improve when neural compressors intentionally distort reconstruction distributions away from mismatched source domains toward a target distribution.
Long-time behaviors in deep linear transformers can reveal surprising dynamics like clustering and oscillations, all rooted in a hidden Hamiltonian structure.
