9 citations · 10 across the 10 of their papers we have counts for
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BEExformer: A Fast Inferencing Binarized Transformer with Early Exits
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
Large Language Models (LLMs) based on transformers achieve cutting-edge results on a variety of applications. However, their enormous size and processing requirements hinder deploy…
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions
Sourav Malakar, Saptarsi Goswami, Amlan Chakrabarti +1
Wind flow can be highly unpredictable and can suffer substantial fluctuations in speed and direction due to the shape and height of hills, mountains, and valleys, making accurate w…
Enhancing Electrocardiogram Signal Analysis Using NLP-Inspired Techniques: A Novel Approach with Embedding and Self-Attention
Prapti Ganguly, Wazib Ansar, Amlan Chakrabarti
A language is made up of an infinite/finite number of sentences, which in turn is composed of a number of words. The Electrocardiogram (ECG) is the most popular noninvasive medical…
TexIm FAST: Text-to-Image Representation for Semantic Similarity Evaluation using Transformers
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
One of the principal objectives of Natural Language Processing (NLP) is to generate meaningful representations from text. Improving the informativeness of the representations has l…
A Survey of Transformer-based Language Models with Focus on Efficiency
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (NLP), thereby intensifying the demand f…