mlsanityData to 7 Oct 2026

A Survey on Neural Network Language Models

arXiv 1906.03591 ↗First posted 9 Jun 2019cs.CL cs.LGcited by 12

Not on the map. Why?

Abstract (arXiv)

As the core component of Natural Language Processing (NLP) system, Language Model (LM) can provide word representation and probability indication of word sequences. Neural Network Language Models (NNLMs) overcome the curse of dimensionality and improve the performance of traditional LMs. A survey on NNLMs is performed in this paper. The structure of classic NNLMs is described firstly, and then some major improvements are introduced and analyzed. We summarize and compare corpora and toolkits of NNLMs. Further, some research directions of NNLMs are discussed.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jun 2019.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 1; 2023: 6; 2024: 1.

12 papers.