The project focuses on controlling text generation through Large Language Models (LLMs) using advanced prompt engineering and knowledge representation. The project aims to improve controllable citation text generation and ...

This research aims to improve the diagnosis of neurodevelopmental disorders by using smartphones, focusing on the psychology of eyes through pupil dynamics analysis. We are developing a user-friendly smartphone app to track ...

Knowledge distillation is a technique that involves transferring knowledge from a larger teacher model to a smaller student model. The latest developments in meta-learning-based knowledge distillation emphasize the ...

Given the facial image of an individual along with audio, Talking face generation aims to synthesize portrait videos of the individual that are conditioned by the given audio. Existing methods focus on generating talking ...

The commercial use of Natural Language Processing (NLP) has gained significant popularity in recent years. Many companies train and deploy language models to perform tasks like Sentiment classification, Machine Translation ...

Unsupervised domain adaptation (UDA) has emerged as a vital research area in the field of machine learning and computer vision. It addresses the challenge of adapting models trained on a labeled source domain to perform ...

The project introduces an innovative method for predicting shock in ICU patients by leveraging unsupervised pre-trained embeddings from vital signs. Utilizing the extensive eICU and MIMIC datasets, the research focuses on ...

Organ transplantation represents a beacon of hope for individuals facing end-stage organ failure, with the success hinging on donor-recipient compatibility. Complement-dependent cytotoxicity (CDC) crossmatch imaging and ...

Visual Question Answering(VQA) has applications in various rising areas ranging from Medical Imagery to Video Surveillance and Assistance[1]. VQA problem is a central component of the Artificial General Intelligence problem, ...