Kaleb E. Smith

According to our database, Kaleb E. Smith authored at least 20 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improving Generalizability of Extracting Social Determinants of Health Using Large Language Models through Prompt-tuning.

Cheng Peng, Zehao Yu, Kaleb E. Smith, Wei-Hsuan Lo-Ciganic, Jiang Bian, Yonghui Wu

CoRR, 2024

2023

A study of generative large language model for medical research and healthcare.

Cheng Peng, Xi Yang, Aokun Chen, Kaleb E. Smith, Nima M. Pournejatian, Anthony B. Costa, Cheryl Martin, Mona G. Flores, Ying Zhang, Tanja Magoc, Gloria P. Lipori, Duane A. Mitchell, Naykky Singh Ospina, Mustafa M. Ahmed, William R. Hogan, Elizabeth A. Shenkman, Yi Guo, Jiang Bian, Yonghui Wu

npj Digit. Medicine, 2023

Generative Large Language Models Are All-purpose Text Analytics Engines: Text-to-text Learning Is All Your Need.

Cheng Peng, Xi Yang, Aokun Chen, Zehao Yu, Kaleb E. Smith, Anthony B. Costa, Mona G. Flores, Jiang Bian, Yonghui Wu

CoRR, 2023

On the Impact of Cross-Domain Data on German Language Models.

Amin Dada, Aokun Chen, Cheng Peng, Kaleb E. Smith, Ahmad Idrissi-Yaghir, Constantin Marc Seibold, Jianning Li, Lars Heiliger, Xi Yang, Christoph M. Friedrich, Daniel Truhn, Jan Egger, Jiang Bian, Jens Kleesiek, Yonghui Wu

CoRR, 2023

Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction.

Cheng Peng, Xi Yang, Kaleb E. Smith, Zehao Yu, Aokun Chen, Jiang Bian, Yonghui Wu

CoRR, 2023

A Study of Generative Large Language Model for Medical Research and Healthcare.

Cheng Peng, Xi Yang, Aokun Chen, Kaleb E. Smith, Nima M. Pournejatian, Anthony B. Costa, Cheryl Martin, Mona G. Flores, Ying Zhang, Tanja Magoc, Gloria P. Lipori, Duane A. Mitchell, Naykky Singh Ospina, Mustafa M. Ahmed, William R. Hogan, Elizabeth Shenkman, Yi Guo, Jiang Bian, Yonghui Wu

CoRR, 2023

On the Impact of Cross-Domain Data on German Language Models.

Amin Dada, Aokun Chen, Cheng Peng, Kaleb E. Smith, Ahmad Idrissi-Yaghir, Constantin Seibold, Jianning Li, Lars Heiliger, Christoph M. Friedrich, Daniel Truhn, Jan Egger, Jiang Bian, Jens Kleesiek, Yonghui Wu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

A large language model for electronic health records.

Xi Yang, Aokun Chen, Nima M. Pournejatian, Hoo Chang Shin, Kaleb E. Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Anthony B. Costa, Mona G. Flores, Ying Zhang, Tanja Magoc, Christopher A. Harle, Gloria P. Lipori, Duane A. Mitchell, William R. Hogan, Elizabeth A. Shenkman, Jiang Bian, Yonghui Wu

npj Digit. Medicine, 2022

Machine Learning Methods Applied to Cortico-Cortical Evoked Potentials Aid in Localizing Seizure Onset Zones.

Ian G. Malone, Kaleb E. Smith, Morgan E. Urdaneta, Tyler S. Davis, Daria Nesterovich Anderson, Brian J. Phillip, John D. Rolston, Christopher R. Butson

CoRR, 2022

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records.

Xi Yang, Nima M. Pournejatian, Hoo Chang Shin, Kaleb E. Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G. Flores, Ying Zhang, Tanja Magoc, Christopher A. Harle, Gloria P. Lipori, Duane A. Mitchell, William R. Hogan, Elizabeth A. Shenkman, Jiang Bian, Yonghui Wu

CoRR, 2022

Space-Based Mapping of Mangrove Canopy Height with Multi-Sensor Observations and Deep Learning Techniques.

Boya Zhang, Kaleb E. Smith, Shimon Wdowinski, Chaohao Lin, Daniel Gann, Selena Chavez, Jingchao Zhang

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021

Building an AI-ready RSE Workforce.

Ying Zhang, Matthew A. Gitzendanner, Dan S. Maxwell, Justin W. Richardson, Kaleb E. Smith, Eric A. Stubbs, Brian J. Stucky, Jingchao Zhang, Erik Deumens

CoRR, 2021

A Spectral Enabled GAN for Time Series Data Generation.

Kaleb E. Smith, Anthony O. Smith

CoRR, 2021

2020

Conditional GAN for timeseries generation.

Kaleb E. Smith, Anthony O. Smith

CoRR, 2020

2019

A Shallow Learning - Reduced Data Approach for Image Classification.

Kaleb E. Smith, Phillip Williams

Proceedings of the Advances in Artificial Intelligence, 2019

2018

Shepard Interpolation Neural Networks with K-Means: A Shallow Learning Method for Time Series Classification.

Kaleb E. Smith, Phillip Williams, Kaylen J. Bryan, Mitchell Solomon, Max Ble, Rana Haber

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Time Series Classification with Shallow Learning Shepard Interpolation Neural Networks.

Kaleb E. Smith, Phillip Williams

Proceedings of the Image and Signal Processing - 8th International Conference, 2018

Deep Convolutional-Shepard Interpolation Neural Networks for Image Classification Tasks.

Kaleb E. Smith, Phillip Williams, Tatsanee Chaiya, Max Ble

Proceedings of the Image Analysis and Recognition - 15th International Conference, 2018

2016

Video Tracking with Probabilistic Cooccurrence Feature Extraction.

Kaleb E. Smith, Anthony O. Smith

Proceedings of the Advances in Visual Computing - 12th International Symposium, 2016

Adaptive Foreground Extraction for Deep Fish Classification.

Nicole Seese, Andrew Myers, Kaleb E. Smith, Anthony O. Smith

Proceedings of the 2nd ICPR Workshop on Computer Vision for Analysis of Underwater Imagery, 2016