356 citations · 362 across the 5 of their papers we have counts for
5 papers
SimplyRetrieve: A Private and Lightweight Retrieval-Centric Generative AI Tool
Youyang Ng, Daisuke Miyashita, Yasuto Hoshi +4
Large Language Model (LLM) based Generative AI systems have seen significant progress in recent years. Integrating a knowledge retrieval architecture allows for seamless integratio…
RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models
Yasuto Hoshi, Daisuke Miyashita, Youyang Ng +4
Retrieval-augmented large language models (R-LLMs) combine pre-trained large language models (LLMs) with information retrieval systems to improve the accuracy of factual question-a…
Can a Frozen Pretrained Language Model be used for Zero-shot Neural Retrieval on Entity-centric Questions?
Yasuto Hoshi, Daisuke Miyashita, Yasuhiro Morioka +3
Neural document retrievers, including dense passage retrieval (DPR), have outperformed classical lexical-matching retrievers, such as BM25, when fine-tuned and tested on specific q…
Revisiting a kNN-based Image Classification System with High-capacity Storage
Kengo Nakata, Youyang Ng, Daisuke Miyashita +3
In existing image classification systems that use deep neural networks, the knowledge needed for image classification is implicitly stored in model parameters. If users want to upd…
Convolutional Neural Networks using Logarithmic Data Representation
Daisuke Miyashita, Edward H. Lee, Boris Murmann
Recent advances in convolutional neural networks have considered model complexity and hardware efficiency to enable deployment onto embedded systems and mobile devices. For example…