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Found 7 papers, 1 papers with code
Introducing the Hidden Neural Markov Chain framework
However, if many works create extensions and improvements of the RNN, few have focused on developing other ways for sequential data processing with neural networks in a "term-to-term" way.
Highly Fast Text Segmentation With Pairwise Markov Chains
Natural Language Processing (NLP) models' current trend consists of using increasingly more extra-data to build the best models as possible.
Hidden Markov Chains, Entropic Forward-Backward, and Part-Of-Speech Tagging
We illustrate the efficiency of HMC using EFB in Part-Of-Speech Tagging, showing its superiority over MEMM based restoration.
Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
The dominant approaches to text representation in natural language rely on learning embeddings on massive corpora which have convenient properties such as compositionality and distance preservation.
Ranked #3 on
Sentiment Analysis
on Yelp Binary classification
Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue
The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents.
Guiding attention in Sequence-to-sequence models for Dialogue Act prediction
The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents.
Ranked #1 on
Dialogue Act Classification
on Switchboard corpus
