Sequence Modeling

2 items

RESEARCHarXiv CS.CL·4/8/2026

Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space

O artigo apresenta a Memória Associativa de Fase (PAM), um modelo de sequência recorrente que utiliza representações de valores complexos e opera em um espaço de Hilbert complexo. O PAM alcança uma perplexidade de validação de 30.0 no WikiText-103, um desempenho competitivo com transformadores, e aborda a degradação da capacidade em modelos de estado vetorial.

Associative Memory Phase-Associative Memory Sequence Modeling Complex Hilbert Space

RESEARCHarXiv CS.LG·12d ago

A Simple State Space Model Excels at Multivariate Time Series Classification

This research systematically studies structured state space models (SSMs) for time-series classification, comparing complex Mamba-based architectures with simpler diagonal SSMs (S4D). Surprisingly, S4D consistently outperforms Mamba variants in accuracy and efficiency on large-scale benchmarks, challenging the assumption that increased model complexity leads to better performance in this domain.

Time Series Classification deep learning machine learning Sequence Modeling