5 citations · 10 across the 5 of their papers we have counts for
5 papers
Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models
Zizhang Chen, Peizhao Li, Xiaomeng Dong +1
To facilitate healthcare delivery, language models (LMs) have significant potential for clinical prediction tasks using electronic health records (EHRs). However, in these high-sta…
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141
Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…
Question Rephrasing for Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks
Zizhang Chen, Pengyu Hong, Sandeep Madireddy
Uncertainty quantification enables users to assess the reliability of responses generated by large language models (LLMs). We present a novel Question Rephrasing technique to evalu…
GlycoNMR: Dataset and benchmarks for NMR chemical shift prediction of carbohydrates with graph neural networks
Zizhang Chen, Ryan Paul Badman, Lachele Foley +2
Molecular representation learning (MRL) is a powerful tool for bridging the gap between machine learning and chemical sciences, as it converts molecules into numerical representati…
Characterizing the Influence of Graph Elements
Zizhang Chen, Peizhao Li, Hongfu Liu +1
Influence function, a method from robust statistics, measures the changes of model parameters or some functions about model parameters concerning the removal or modification of tra…