98 citations · 210 across the 8 of their papers we have counts for
4 papers · 1 filter
MergeME: Model Merging Techniques for Homogeneous and Heterogeneous MoEs
Yuhang Zhou, Giannis Karamanolakis, Victor Soto +5
The recent success of specialized Large Language Models (LLMs) in domains such as mathematical reasoning and coding has led to growing interest in methods for merging these expert…
Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine
Yifan Yang, Qiao Jin, Robert Leaman +15
The remarkable capabilities of Large Language Models (LLMs) make them increasingly compelling for adoption in real-world healthcare applications. However, the risks associated with…
Large Language Models and Causal Inference in Collaboration: A Survey
Xiaoyu Liu, Paiheng Xu, Junda Wu +10
Causal inference has shown potential in enhancing the predictive accuracy, fairness, robustness, and explainability of Natural Language Processing (NLP) models by capturing causal…
Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation
Yifan Yang, Xiaoyu Liu, Qiao Jin +2
Large language models like GPT-3.5-turbo and GPT-4 hold promise for healthcare professionals, but they may inadvertently inherit biases during their training, potentially affecting…