1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2026
Multi-Modal Multi-Agent Reinforcement Learning for Radiology Report Generation
Kaito Baba, Risa Kishikawa, Satoshi Kodera
We propose MARL-Rad, a multi-modal multi-agent reinforcement learning framework for radiology report generation that trains the entire agentic system on policy within its deployed…
cs.CV2024
JRadiEvo: A Japanese Radiology Report Generation Model Enhanced by Evolutionary Optimization of Model Merging
Kaito Baba, Ryota Yagi, Junichiro Takahashi +2
With the rapid advancement of large language models (LLMs), foundational models (FMs) have seen significant advancements. Healthcare is one of the most crucial application areas fo…
cs.CL2024★ 1 cited
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…