8 citations · 30 across the 34 of their papers we have counts for
5 papers · 2 filters
MedBench: A Comprehensive, Standardized, and Reliable Benchmarking System for Evaluating Chinese Medical Large Language Models
Mianxin Liu, Jinru Ding, Jie Xu +16
Ensuring the general efficacy and goodness for human beings from medical large language models (LLM) before real-world deployment is crucial. However, a widely accepted and accessi…
MedOdyssey: A Medical Domain Benchmark for Long Context Evaluation Up to 200K Tokens
Yongqi Fan, Hongli Sun, Kui Xue +3
Numerous advanced Large Language Models (LLMs) now support context lengths up to 128K, and some extend to 200K. Some benchmarks in the generic domain have also followed up on evalu…
Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges
Xiaoming Shi, Zeming Liu, Li Du +6
This paper surveys and organizes research works on medical dialog systems, which is an important yet challenging task. Although these systems have been surveyed in the medical comm…
Tool Calling: Enhancing Medication Consultation via Retrieval-Augmented Large Language Models
Zhongzhen Huang, Kui Xue, Yongqi Fan +5
Large-scale language models (LLMs) have achieved remarkable success across various language tasks but suffer from hallucinations and temporal misalignment. To mitigate these shortc…
Evaluating and Enhancing Large Language Models Performance in Domain-specific Medicine: Osteoarthritis Management with DocOA
Xi Chen, MingKe You, Li Wang +7
The efficacy of large language models (LLMs) in domain-specific medicine, particularly for managing complex diseases such as osteoarthritis (OA), remains largely unexplored. This s…