lstm-recognizes-context-sensitive-languages

IN premise — entries/2026/06/21/wiki-Recurrent_neural_network-chunk-3.md

Created 2026-06-21T09:55:53+00:00

LSTM can recognize context-sensitive languages, surpassing HMM-based models which are limited to regular languages.

Dependents

These beliefs depend on this one:

• IN rnn-theoretical-power-exceeded-practical-utility — RNNs possess strong theoretical computational power — Turing-completeness with rational weights (Siegelmann & Sontag 1994) and context-sensitive language recognition via LSTM that surpasses what HMM-based models achieve — while their sequential hidden-state processing, which updates state at each time step, represents an inherent constraint on parallelism.