5 papers
Fine-Tuning Large Language Models for Quantum Reasoning
Katherine Ip, Casey R. Myers, Udaya Parampalli +2
Large language models (LLMs) exhibit abilities beyond natural language modelling and text generation. Recent advances in their reasoning capabilities have spurred interest in apply…
A System Aware Resource Allocation for Distributed Workflows in Quantum Computing Environments
Abhishek Sawaika, Udaya Parampalli, Rajkumar Buyya
Rapid advancements in cloud based platforms providing access to quantum computing capabilities have opened up several challenges for efficient usage of these highly delicate and co…
Federated Learning with Quantum Enhanced LSTM for Applications in High Energy Physics
Abhishek Sawaika, Durga Pritam Suggisetti, Udaya Parampalli +1
Learning with large-scale datasets and information-critical applications, such as in High Energy Physics (HEP), demands highly complex, large-scale models that are both robust and…
MADQRL: Distributed Quantum Reinforcement Learning Framework for Multi-Agent Environments
Abhishek Sawaika, Samuel Yen-Chi Chen, Udaya Parampalli +1
Reinforcement learning (RL) is one of the most practical ways to learn from real-life use-cases. Motivated from the cognitive methods used by humans makes it a widely acceptable st…
Binary cyclic codes from permutation polynomials over
Mrinal Kanti Bose, Udaya Parampalli, Abhay Kumar Singh
Binary cyclic codes having large dimensions and minimum distances close to the square-root bound are highly valuable in applications where high-rate transmission and robust error c…