Abstract: Prompt-based learning has demonstrated remarkable success in few-shot text classification, outperforming the traditional fine-tuning approach. This method transforms a text input into a ...
Abstract: Deep learning-based methods have shown promising results in multi-label chest X-ray (CXR) image classification. However, most existing methods rely on large-scale fully-annotated datasets, ...
For this report, Reddit posts and comments were classified using the following prompts to GPT-4.1 mini. The prompts were designed to mirror the codebooks that our research team used to create the ...
The International Classification of Diseases, or ICD, is a classification system for all physical and mental diseases produced by the World Health Organization (WHO). It’s used for diagnosis, research ...
NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...
Section 1. Purpose. Across the country, ideologues who deny the biological reality of sex have increasingly used legal and other socially coercive means to permit men to self-identify as women and ...
If you want a straightforward document about the wine you’re about to drink, its label may not be that helpful. As we’ve discussed before with the opaque world of “reserve” and “grand reserve,” “grand ...
The basic principles required to solve classification tasks with neural networks are used as building blocks in more complicated deep learning problems such as object detection and instance ...
Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...
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