Framework for deep learning-based language models using multi-task learning in natural language understanding: A systematic literature review and future directions
Learning human languages is a difficult task for a computer. However, Deep Learning (DL)
techniques have enhanced performance significantly for almost all-natural language …
techniques have enhanced performance significantly for almost all-natural language …
Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation
Inducing diversity in the task of paraphrasing is an important problem in NLP with
applications in data augmentation and conversational agents. Previous paraphrasing …
applications in data augmentation and conversational agents. Previous paraphrasing …
Chatbot Interaction with Artificial Intelligence: human data augmentation with T5 and language transformer ensemble for text classification
In this work we present the Chatbot Interaction with Artificial Intelligence (CI-AI) framework
as an approach to the training of a transformer based chatbot-like architecture for task …
as an approach to the training of a transformer based chatbot-like architecture for task …
Voice for the voiceless: Active sampling to detect comments supporting the rohingyas
S Palakodety, AR KhudaBukhsh… - Proceedings of the AAAI …, 2020 - aaai.org
The Rohingya refugee crisis is one of the biggest humanitarian crises of modern times with
more than 700,000 Rohingyas rendered homeless according to the United Nations High …
more than 700,000 Rohingyas rendered homeless according to the United Nations High …
Harnessing code switching to transcend the linguistic barrier
AR KhudaBukhsh, S Palakodety… - arXiv preprint arXiv …, 2020 - arxiv.org
Code mixing (or code switching) is a common phenomenon observed in social-media
content generated by a linguistically diverse user-base. Studies show that in the Indian sub …
content generated by a linguistically diverse user-base. Studies show that in the Indian sub …
Deep active learning for sequence labeling based on diversity and uncertainty in gradient
Y Kim - arXiv preprint arXiv:2011.13570, 2020 - arxiv.org
Recently, several studies have investigated active learning (AL) for natural language
processing tasks to alleviate data dependency. However, for query selection, most of these …
processing tasks to alleviate data dependency. However, for query selection, most of these …
Opinion subset selection via submodular maximization
Current research on subset selection for opinion analysis assumes that their methods can
retrieve the opinions expressed in documents from general text features. However, such …
retrieve the opinions expressed in documents from general text features. However, such …
A Study on the Impacts of Slot Types and Training Data on Joint Natural Language Understanding in a Spanish Medication Management Assistant Scenario
This study evaluates the impacts of slot tagging and training data length on joint natural
language understanding (NLU) models for medication management scenarios using …
language understanding (NLU) models for medication management scenarios using …
A multitask active learning framework for natural language understanding
H Zhu, W Ye, S Luo, X Zhang - Proceedings of the 28th …, 2020 - aclanthology.org
Natural language understanding (NLU) aims at identifying user intent and extracting
semantic slots. This requires sufficient annotating data to get considerable performance in …
semantic slots. This requires sufficient annotating data to get considerable performance in …
The refugee experience online: Surfacing positivity amidst hate
S Palakodety, AR KhudaBukhsh, JG Carbonell - ECAI 2020, 2020 - ebooks.iospress.nl
Abstract How can Artificial Intelligence help a stateless minority from online abuse?
Research efforts in hate speech detection thus far have largely focused on identifying and …
Research efforts in hate speech detection thus far have largely focused on identifying and …