Review - STAR framework and ASP programming for NLU Tasks-part 2: Solving Word Problems in Algebra
Our follow up on the STAR Framework, this time showing how to solve word problems in algebra in Python.
Our follow up on the STAR Framework, this time showing how to solve word problems in algebra in Python.
In part one of this review series, we look at the STAR framework and assess its capabilities for taking on Natural Language Understanding tasks.
In this article, we examine the theoretical design behind the popular Transformers architecture, and attempt to explain the underlying mechanisms that have lead to its success in such a wide array of AI disciplines.
In this review, we examine popular text summarization models, and compare and contrast their capabilities for use in our own work.
This review covers different methodologies for open-ended text generation
Follow this guide to create a conversational system with a pretrained LLM in Paperspace.
This is a review of the CausalML package, a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research.
In this theory we cover the background theory behind a variety of methodologies for abstractive text summarization
In this article, we take a theoretical lens to the PP-YOLO model, breakdown its model architecture in detail, and compare its features to those of its predecessor YOLO family models.