3 citations · 7 across the 4 of their papers we have counts for
4 papers
Quantum Transformer: Accelerating model inference via quantum linear algebra
Naixu Guo, Zhan Yu, Matthew Choi +5
Powerful generative artificial intelligence from large language models (LLMs) harnesses extensive computational resources for inference. In this work, we investigate the transforme…
Large Language Models on Lexical Semantic Change Detection: An Evaluation
Ruiyu Wang, Matthew Choi
Lexical Semantic Change Detection stands out as one of the few areas where Large Language Models (LLMs) have not been extensively involved. Traditional methods like PPMI, and SGNS…
FlexModel: A Framework for Interpretability of Distributed Large Language Models
Matthew Choi, Muhammad Adil Asif, John Willes +1
With the growth of large language models, now incorporating billions of parameters, the hardware prerequisites for their training and deployment have seen a corresponding increase.…
Machine learning of measurement schemes for efficient quantum observable estimation
Zi-Jian Zhang, Kouhei Nakaji, Matthew Choi +1
Estimation of the expectation value of observables is a key subroutine in quantum computing and is also the bottleneck of the performance of many near-term quantum algorithms. Many…