Technical Workshop Series - Introduction to Large Language Models (1st Offering) by Zahra Taherikhonakdar

A language model is a probabilistic representation of a natural language. It can estimate the likelihood of word sequences based on the textual data it was trained on, encompassing one or more languages. The initial significant statistical language model emerged in 1980, followed by IBM's 'Shannon-style' experiments in the same decade. These experiments involved observing and analyzing human subjects' performance in predicting or correcting text, leading to the identification of potential avenues for enhancing language modelling.

These models find application in various tasks, such as speech recognition (aiding in avoiding predictions of improbable or nonsensical sequences), machine translation, natural language generation (producing text that resembles human language more closely), optical character recognition, handwriting recognition, grammar induction, and information retrieval.

 

In this workshop, you will be introduced to language models:

- Introduction to LLMs

- Introducing models

- Introducing the models' techniques

 

Computer Science knowledge

 

Zahra is a PhD student at the University of Windsor. Her research is in the area of Information Retrieval. Mainly her research is about how to improve query refinement as a technique to make search engines to retrieve the most related documents based on users' initial query.