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View article: GAN-LM: Generative Adversarial Network using Language Models for Downstream Applications
GAN-LM: Generative Adversarial Network using Language Models for Downstream Applications Open
In this work, we investigate Data Augmentation methods to improve the performance of state-of-the-art models for four different downstream tasks. Specifically, we propose Generative Adversarial Network using Language Models (GAN-LM) approa…
View article: Towards Multi-Objective Statistically Fair Federated Learning
Towards Multi-Objective Statistically Fair Federated Learning Open
Federated Learning (FL) has emerged as a result of data ownership and privacy concerns to prevent data from being shared between multiple parties included in a training procedure. Although issues, such as privacy, have gained significant a…
View article: Meta-Learning for Few-Shot Named Entity Recognition
Meta-Learning for Few-Shot Named Entity Recognition Open
Meta-learning has recently been proposed to learn models and algorithms that can generalize from a handful of examples. However, applications to structured prediction and textual tasks pose challenges for meta-learning algorithms. In this …
View article: A Closer Look At Feature Space Data Augmentation For Few-Shot Intent\n Classification
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent\n Classification Open
New conversation topics and functionalities are constantly being added to\nconversational AI agents like Amazon Alexa and Apple Siri. As data collection\nand annotation is not scalable and is often costly, only a handful of examples\nfor t…
View article: A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification Open
New conversation topics and functionalities are constantly being added to conversational AI agents like Amazon Alexa and Apple Siri. As data collection and annotation is not scalable and is often costly, only a handful of examples for the …