5 citations · 8 across the 3 of their papers we have counts for
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cs.CL2018
Multi-Layer Ensembling Techniques for Multilingual Intent Classification
Charles Costello, Ruixi Lin, Vishwas Mruthyunjaya +2
In this paper we determine how multi-layer ensembling improves performance on multilingual intent classification. We develop a novel multi-layer ensembling approach that ensembles…
cs.CL2018
Combining Word Feature Vector Method with the Convolutional Neural Network for Slot Filling in Spoken Language Understanding
Ruixi Lin
Slot filling is an important problem in Spoken Language Understanding (SLU) and Natural Language Processing (NLP), which involves identifying a user's intent and assigning a semant…
cs.CL2018
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques
Ruixi Lin, Charles Costello, Charles Jankowski
Intent classification has been widely researched on English data with deep learning approaches that are based on neural networks and word embeddings. The challenge for Chinese inte…