6 citations · 12 across the 7 of their papers we have counts for
7 papers
Aligning Language Models with Selective Prediction
Gaoxiang Luo, Yifan Wu, Sinian Zhang +2
Large language models (LLMs) are increasingly deployed as critical decision-making components in high-stakes real-world AI systems, rendering LLM reliability a foremost practical c…
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing
Le Peng, Gaoxiang Luo, sicheng zhou +4
Language models (LMs) such as BERT and GPT have revolutionized natural language processing (NLP). However, the medical field faces challenges in training LMs due to limited data ac…
A Cross-institutional Evaluation on Breast Cancer Phenotyping NLP Algorithms on Electronic Health Records
Sicheng Zhou, Nan Wang, Liwei Wang +4
Objective: The generalizability of clinical large language models is usually ignored during the model development process. This study evaluated the generalizability of BERT-based c…
Welfare and Fairness Dynamics in Federated Learning: A Client Selection Perspective
Yash Travadi, Le Peng, Xuan Bi +2
Federated learning (FL) is a privacy-preserving learning technique that enables distributed computing devices to train shared learning models across data silos collaboratively. Exi…
Imbalanced Classification in Medical Imaging via Regrouping
Le Peng, Yash Travadi, Rui Zhang +2
We propose performing imbalanced classification by regrouping majority classes into small classes so that we turn the problem into balanced multiclass classification. This new idea…
A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals
Ju Sun, Le Peng, Taihui Li +14
Importance: An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate cli…