5 papers
JMed48k: A Multi-Profession Japanese Medical Licensing Benchmark for Vision-Language Model Evaluation
Yue Xun, Junyu Liu, Qian Niu +10
We introduce JMed48k, a multi-profession Japanese healthcare licensing benchmark for evaluating vision-language models. Built from official PDF materials released by the Japanese M…
JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese Large Language Models
Junyu Liu, Zirui Li, Qian Niu +7
As Large Language Models (LLMs) are increasingly deployed in healthcare field, it becomes essential to carefully evaluate their medical safety before clinical use. However, existin…
Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research
Kan Hatakeyama-Sato, Toshihiko Nishida, Kenta Kitamura +4
This review explores the potential of foundation models to advance laboratory automation in the materials and chemical sciences. It emphasizes the dual roles of these models: cogni…
SPACIER: On-Demand Polymer Design with Fully Automated All-Atom Classical Molecular Dynamics Integrated into Machine Learning Pipelines
Shun Nanjo, Arifin, Hayato Maeda +5
Machine learning has rapidly advanced the design and discovery of new materials with targeted applications in various systems. First-principles calculations and other computer expe…
Teaching Specific Scientific Knowledge into Large Language Models through Additional Training
Kan Hatakeyama-Sato, Yasuhiko Igarashi, Shun Katakami +2
Through additional training, we explore embedding specialized scientific knowledge into the Llama 2 Large Language Model (LLM). Key findings reveal that effective knowledge integra…