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Found 8 papers, 1 papers with code
Understanding the Properties of Generated Corpora
Models for text generation have become focal for many research tasks and especially for the generation of sentence corpora.
A new data augmentation method for intent classification enhancement and its application on spoken conversation datasets
The NNSI reduces the need for manual labeling by automatically selecting highly-ambiguous samples and labeling them with high accuracy.
Improved Goal Oriented Dialogue via Utterance Generation and Look Ahead
We show that intent prediction can be improved by training a deep text-to-text neural model to generate successive user utterances from unlabeled dialogue data.
Balancing via Generation for Multi-Class Text Classification Improvement
Data balancing is a known technique for improving the performance of classification tasks.
Unsupervised FAQ Retrieval with Question Generation and BERT
The two models match user queries to FAQ answers and questions, respectively.
Not Enough Data? Deep Learning to the Rescue!
Based on recent advances in natural language modeling and those in text generation capabilities, we propose a novel data augmentation method for text classification tasks.
Neural network gradient-based learning of black-box function interfaces
We propose a method for end-to-end training of a base neural network that integrates calls to existing black-box functions.
Estimate and Replace: A Novel Approach to Integrating Deep Neural Networks with Existing Applications
At inference time, we replace each estimator with its existing application counterpart and let the base network solve the task by interacting with the existing application.
