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Found 9 papers, 1 papers with code
Long-Short Range Context Neural Networks for Language Modeling
The goal of language modeling techniques is to capture the statistical and structural properties of natural languages from training corpora.
Sequential Recurrent Neural Networks for Language Modeling
Feedforward Neural Network (FNN)-based language models estimate the probability of the next word based on the history of the last N words, whereas Recurrent Neural Networks (RNN) perform the same task based only on the last word and some context information that cycles in the network.
Sub-Word Similarity based Search for Embeddings: Inducing Rare-Word Embeddings for Word Similarity Tasks and Language Modelling
We augmented pre-trained word embeddings with these novel embeddings and evaluated on a rare word similarity task, obtaining up to 3 times improvement in correlation over the original set of embeddings.
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