adaptive-patching

This paper theoretically and empirically examines adaptive patching for time-series Transformers, deriving conditions under which content-adaptive tokenization should outperform tuned uniform patching. Controlled experiments on standard benchmarks show that a well-tuned uniform baseline is competitive with dynamic patching methods, challenging the assumed benefit of adaptive approaches.