129 citations · 306 across the 13 of their papers we have counts for
22 papers
Using Random Perturbations to Mitigate Adversarial Attacks on Sentiment Analysis Models
Abigail Swenor, Jugal Kalita
Attacks on deep learning models are often difficult to identify and therefore are difficult to protect against. This problem is exacerbated by the use of public datasets that typic…
Neural Twins Talk & Alternative Calculations
Zanyar Zohourianshahzadi, Jugal K. Kalita
Inspired by how the human brain employs a higher number of neural pathways when describing a highly focused subject, we show that deep attentive models used for the main vision-lan…
Language Model Metrics and Procrustes Analysis for Improved Vector Transformation of NLP Embeddings
Thomas Conley, Jugal Kalita
Artificial Neural networks are mathematical models at their core. This truismpresents some fundamental difficulty when networks are tasked with Natural Language Processing. A key p…
Solving Arithmetic Word Problems with Transformers and Preprocessing of Problem Text
Kaden Griffith, Jugal Kalita
This paper outlines the use of Transformer networks trained to translate math word problems to equivalent arithmetic expressions in infix, prefix, and postfix notations. We compare…
Classifying Malware Images with Convolutional Neural Network Models
Ahmed Bensaoud, Nawaf Abudawaood, Jugal Kalita
Due to increasing threats from malicious software (malware) in both number and complexity, researchers have developed approaches to automatic detection and classification of malwar…
Multi-task learning for natural language processing in the 2020s: where are we going?
Joseph Worsham, Jugal Kalita
Multi-task learning (MTL) significantly pre-dates the deep learning era, and it has seen a resurgence in the past few years as researchers have been applying MTL to deep learning s…