12 citations · 22 across the 11 of their papers we have counts for
12 papers
LimeCross: Context-Conditioned Layered Image Editing with Structural Consistency
Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +4
Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances in layered image generation a…
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…
Relative local dependence of bivariate copulas
Issey Sukeda, Tomonari Sei
For a bivariate probability distribution, local dependence around a single point on the support is often formulated as the second derivative of the logarithm of the probability den…
70B-parameter large language models in Japanese medical question-answering
Issey Sukeda, Risa Kishikawa, Satoshi Kodera
Since the rise of large language models (LLMs), the domain adaptation has been one of the hot topics in various domains. Many medical LLMs trained with English medical dataset have…
Frank copula is minimum information copula under fixed Kendall's
Issey Sukeda, Tomonari Sei
In dependence modeling, various copulas have been utilized. Among them, the Frank copula has been one of the most typical choices due to its simplicity. In this work, we demonstrat…
JMedLoRA:Medical Domain Adaptation on Japanese Large Language Models using Instruction-tuning
Issey Sukeda, Masahiro Suzuki, Hiroki Sakaji +1
In the ongoing wave of impact driven by large language models (LLMs) like ChatGPT, the adaptation of LLMs to medical domain has emerged as a crucial research frontier. Since mainst…
On the minimum information checkerboard copulas under fixed Kendall's rank correlation
Issey Sukeda, Tomonari Sei
Copulas have gained widespread popularity as statistical models to represent dependence structures between multiple variables in various applications. The minimum information copul…
A Study on Modularity Density Maximization: Column Generation Acceleration and Computational Complexity Analysis
Issey Sukeda, Atsushi Miyauchi, Akiko Takeda
Community detection is a fundamental network-analysis primitive with a variety of applications in diverse domains. Although the modularity introduced by Newman and Girvan (2004) ha…