Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

This is the code for Pl@ntBERT, the framework of the paper Learning the syntax of plant assemblages published in Open Access in Nature Plants. If you use this code for your work and wish to credit the ...

Abstract: Hierarchical Text Classification (HTC) is a challenging task where labels are structured in a tree or Directed Acyclic Graph (DAG) format. Current approaches often struggle with data ...

Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language generation.

EleutherAI, an AI research organization, has released what it claims is one of the largest collections of licensed and open-domain text for training AI models. The dataset, called the Common Pile v0.1 ...

In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...

1 School of Media & Communication Shanghai Jiao Tong University, Shanghai, China 2 Department of Critical Care Medicine, Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, China Objective: This study ...

This experiment investigates a text classification problem using a dataset of real and fake facts created by a generative AI tool. While fake news detection often involves complex NLP techniques, this ...

Abstract: Text classification tasks aim to comprehend and classify text content into specific classifications. This task is crucial for interpreting unstructured text, making it a foundational task in ...