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20192022
most citedEfficient Feature Selection techniques for Sentiment Analysis

9 citations · 19 across the 7 of their papers we have counts for

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cs.CL2022

What do Large Language Models Learn beyond Language?

Avinash Madasu, Shashank Srivastava

Large language models (LMs) have rapidly become a mainstay in Natural Language Processing. These models are known to acquire rich linguistic knowledge from training on large amount…

cs.CL2022

A Unified Framework for Emotion Identification and Generation in Dialogues

Avinash Madasu, Mauajama Firdaus, Asif Eqbal

Social chatbots have gained immense popularity, and their appeal lies not just in their capacity to respond to the diverse requests from users, but also in the ability to develop a…

cs.CL2020

Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment Analysis

Avinash Madasu, Vijjini Anvesh Rao

Elastic Weight Consolidation (EWC) is a technique used in overcoming catastrophic forgetting between successive tasks trained on a neural network. We use this phenomenon of informa…

cs.CL2020

A Position Aware Decay Weighted Network for Aspect based Sentiment Analysis

Avinash Madasu, Vijjini Anvesh Rao

Aspect Based Sentiment Analysis (ABSA) is the task of identifying sentiment polarity of a text given another text segment or aspect. In ABSA, a text can have multiple sentiments de…

cs.CL20199 cited

Efficient Feature Selection techniques for Sentiment Analysis

Avinash Madasu, Sivasankar E

Sentiment analysis is a domain of study that focuses on identifying and classifying the ideas expressed in the form of text into positive, negative and neutral polarities. Feature…

cs.CL2019

Sequential Learning of Convolutional Features for Effective Text Classification

Avinash Madasu, Vijjini Anvesh Rao

Text classification has been one of the major problems in natural language processing. With the advent of deep learning, convolutional neural network (CNN) has been a popular solut…