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- Temple CollegeUS66 papers
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8 papers · 1 filter
Use GPT-J Prompt Generation with RoBERTa for NER Models on Diagnosis Extraction of Periodontal Diagnosis from Electronic Dental Records
Yao-Shun Chuang, Xiaoqian Jiang, Chun-Teh Lee +4
This study explored the usability of prompt generation on named entity recognition (NER) tasks and the performance in different settings of the prompt. The prompt generation by GPT…
Measurement of the Generalized Polarizabilities of the Proton in Virtual Compton Scattering
H. Atac, A. Camsonne, M. K. Jones +37
We propose to conduct a measurement of the Virtual Compton Scattering reaction in Hall C that will allow the precise extraction of the two scalar Generalized Polarizabilities (GPs)…
Understanding the Anomalous Diffusion of Water in Aqueous Electrolytes Using Machine Learned Potentials
Nikhil V. S. Avula, Michael L. Klein, Sundaram Balasubramanian
The diffusivity of water in aqueous cesium iodide solutions is larger than that in neat liquid water, and vice versa for sodium chloride solutions. Such peculiar ion-specific behav…
Freeform Templates: Combining Freeform Curation with Structured Templates
Stephen MacNeil, Ziheng Huang, Kenneth Chen +4
Online whiteboards are becoming a popular way to facilitate collaborative design work, providing a free-form environment to curate ideas. However, as templates are increasingly bei…
Graph Convolutional Networks based on Manifold Learning for Semi-Supervised Image Classification
Lucas Pascotti Valem, Daniel Carlos Guimarães Pedronette, Longin Jan Latecki
Due to a huge volume of information in many domains, the need for classification methods is imperious. In spite of many advances, most of the approaches require a large amount of l…
Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learning
Lucas Pascotti Valem, Daniel Carlos Guimarães Pedronette, Longin Jan Latecki
Impressive advances in acquisition and sharing technologies have made the growth of multimedia collections and their applications almost unlimited. However, the opposite is true fo…