Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...
Background: Accurate documentation of clinical teaching sessions is critical, particularly in multilingual contexts. Recent advances in smartphone-based speech recognition and large language models ...
Abstract: Text summarization, which is the process of making a brief summary of text while preserving its overall meaning, is an important problem in Natural Language Processing (NLP). Automatic ...
Introduction: Plant phenotyping is a critical area in agricultural research that focuses on assessing plant traits quantitatively to enhance productivity and sustainability. While traditional methods ...
Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...
ABSTRACT: This work explores generative AI-enhanced text-based games for language learning. Utilizing ChatGPT, the study modifies an early version of Colossal Cave Adventure to generate contextually ...
Abstract: This project focused on using clinical text data from the PubMed dataset to train transformer models and deep learning models for text summarization. The primary goal was to develop a system ...
Sometime in the 1960s, hypertext pioneer Ted Nelson envisioned deep linking to specific pieces of text as a core feature of his proposed Project Xanadu system. (My first exposure to Xanadu came in the ...
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