4 papers
RankLLM: Weighted Ranking of LLMs by Quantifying Question Difficulty
Ziqian Zhang, Xingjian Hu, Yue Huang +8
Benchmarks establish a standardized evaluation framework to systematically assess the performance of large language models (LLMs), facilitating objective comparisons and driving ad…
QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
Dehai Min, Kailin Zhang, Tongtong Wu +1
Dynamic Retrieval-Augmented Generation adaptively determines when to retrieve during generation to mitigate hallucinations in large language models (LLMs). However, existing method…
Fact or Guesswork? Evaluating Large Language Models' Medical Knowledge with Structured One-Hop Judgments
Jiaxi Li, Yiwei Wang, Kai Zhang +5
Large language models (LLMs) have been widely adopted in various downstream task domains. However, their abilities to directly recall and apply factual medical knowledge remains un…
Structured Outputs Enable General-Purpose LLMs to be Medical Experts
Guangfu Guo, Kai Zhang, Bryan Hoo +4
Medical question-answering (QA) is a critical task for evaluating how effectively large language models (LLMs) encode clinical knowledge and assessing their potential applications…