2 citations · 3 across the 4 of their papers we have counts for
4 papers
Evaluation of Contextual Understanding in Large Language Models
Subavarshana Arumugam, Mamta Nallaretnam, Kithuni Wickramasinghe +4
Large Language Models (LLMs) demonstrate impressive performance across diverse NLP tasks, yet their ability to exhibit genuine contextual understanding remains uncertain. Tradition…
A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals
Pragatheeswaran Vipulanandan, Kamal Premaratne, Manohar Murthi
For seemless control of advanced hand prostheses and augmented reality, accurate and immediate hand gestures recognition is essential. Surface electromyography (sEMG) signals obtai…
Semantic Uncertainty Quantification of Hallucinations in LLMs: A Quantum Tensor Network Based Method
Pragatheeswaran Vipulanandan, Kamal Premaratne, Dilip Sarkar
Large language models (LLMs) exhibit strong generative capabilities but remain vulnerable to confabulations, fluent yet unreliable outputs that vary arbitrarily even under identica…
A Quantum Tensor Network-Based Viewpoint for Modeling and Analysis of Time Series Data
Pragatheeswaran Vipulananthan, Kamal Premaratne, Dilip Sarkar +1
Accurate uncertainty quantification is a critical challenge in machine learning. While neural networks are highly versatile and capable of learning complex patterns, they often lac…