5 papers
Minimum information Markov model
Issey Sukeda, Tomonari Sei
The analysis of high-dimensional time series data has become increasingly important across a wide range of fields. Recently, a method for constructing the minimum information Marko…
Interpreting Multi-Attribute Confounding through Numerical Attributes in Large Language Models
Hirohane Takagi, Gouki Minegishi, Shota Kizawa +2
Although behavioral studies have documented numerical reasoning errors in large language models (LLMs), the underlying representational mechanisms remain unclear. We hypothesize th…
A Japanese Language Model and Three New Evaluation Benchmarks for Pharmaceutical NLP
Shinnosuke Ono, Issey Sukeda, Takuro Fujii +2
We present a Japanese domain-specific language model for the pharmaceutical field, developed through continual pretraining on 2 billion Japanese pharmaceutical tokens and 8 billion…
Exploring the Role of Knowledge Graph-Based RAG in Japanese Medical Question Answering with Small-Scale LLMs
Yingjian Chen, Feiyang Li, Xingyu Song +5
Large language models (LLMs) perform well in medical QA, but their effectiveness in Japanese contexts is limited due to privacy constraints that prevent the use of commercial model…
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resources
Issey Sukeda
The recent success of large language models (LLMs) and the scaling law has led to a widespread adoption of larger models. Particularly in the healthcare industry, there is an incre…