most citedZero-Resource Hallucination Prevention for Large Language Models

11 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL202311 cited

Zero-Resource Hallucination Prevention for Large Language Models

Junyu Luo, Cao Xiao, Fenglong Ma

The prevalent use of large language models (LLMs) in various domains has drawn attention to the issue of "hallucination," which refers to instances where LLMs generate factually in…

cs.LG2023

TREEMENT: Interpretable Patient-Trial Matching via Personalized Dynamic Tree-Based Memory Network

Brandon Theodorou, Cao Xiao, Jimeng Sun

Clinical trials are critical for drug development but often suffer from expensive and inefficient patient recruitment. In recent years, machine learning models have been proposed f…

cs.AI20232 cited

FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection

Brandon Theodorou, Lucas Glass, Cao Xiao +1

Despite many efforts to address the disparities, the underrepresentation of gender, racial, and ethnic minorities in clinical trials remains a problem and undermines the efficacy o…

cs.LG20232 cited

SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning

Zifeng Wang, Cao Xiao, Jimeng Sun

Clinical trials are essential to drug development but time-consuming, costly, and prone to failure. Accurate trial outcome prediction based on historical trial data promises better…

cs.LG2023

Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control

Zhen Lin, Shubhendu Trivedi, Cao Xiao +1

Many real-world multi-label prediction problems involve set-valued predictions that must satisfy specific requirements dictated by downstream usage. We focus on a typical scenario…

cs.LG2021

MedAttacker: Exploring Black-Box Adversarial Attacks on Risk Prediction Models in Healthcare

Muchao Ye, Junyu Luo, Guanjie Zheng +3

Deep neural networks (DNNs) have been broadly adopted in health risk prediction to provide healthcare diagnoses and treatments. To evaluate their robustness, existing research cond…