The AFCAT stands for Air Force Common Admission Test, which is organized at the national level by the Indian Air Force. The test is conducted two times a year for selection in various departments such ...

The Algorithmic Impact Assessment (AIA) is a mandatory risk assessment tool intended to support the Treasury Board’s Directive on Automated Decision-Making. The tool is a questionnaire that determines ...

Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. The ...

OpenAI and Google DeepMind demonstrated that their foundation models could outperform human coders — and win — showing that large language models (LLMs) can solve complex, previously unsolved ...

This repository contains the implementation of RaKUn 2.0, a very fast keyphrase extraction algorithm suitable for large-scale keyphrase retrieval. Running LLMs on massive corpora remains somewhat ...

In a time of societal polarization, the combination of people’s search habits and the search tools they use being optimized for relevance may perpetuate echo chambers. We document this across various ...

Abstract: A substation knowledge graph intelligent Q&A algorithm based on deep learning was designed to provide users with more effective self-service Q&A services. The algorithm first performs power ...

Objective Reducing backlogs for elective care is a priority for healthcare systems. We conducted an interrupted time series analysis demonstrating the effect of an algorithm for placing automatic test ...

Abstract: This paper mainly studied the automatic test paper generation and scoring problems in university English exams. Firstly, an automatic test paper generation model was established. Then, an ...

We evaluated caBERTnet using a sequestered test data set of 2050 pathology reports with ground truth answers determined by certified tumor registrars. Results: caBERTnet’s accuracies for predicting ...

As the use of machine learning algorithms in health care continues to expand, there are growing concerns about equity, fairness, and bias in the ways in which machine learning models are developed and ...