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cs.LG2026
ALPHABET: A Laplace-Pole History Aggregator with Banked Exponential Transport
Daehwa Ko, JaeHyeon Kim, Oh Seong Kwon +1
Can a sequence model remain competitive with only a few thousand parameters and an explicitly auditable prediction interface? We introduce ALPHABET, a compact linear-time model tha…
cs.LG2026
TESLA: Taylor Expansion of Sinusoidal Learnable Activations
Daehwa Ko, Jaehyeon Kim, Seunghyun Ham +1
The parity problem--deciding whether the number of ones in a binary vector is odd or even--remains challenging for standard neural networks due to linear inseparability and the nee…