CPSC 6792Language Model And Processing

Catalog

Natural Language Processing (NLP) stands as a significant branch of artificial intelligence dedicated to equipping computers with the capability to comprehend, interpret, and manipulate human language. NLP encompasses a range of tasks, such as question answering, text classification (including fake detection), text summarization, text generation (including dialogue, translation, and program synthesis), natural language inference, and knowledge base completion. Modern approaches to these tasks heavily rely on statistical language models. The initial segment of this course delves into the evolution of deep neural network language models. The journey begins with the progresses through feed-forward neural networks, recurrent neural networks, and culminates in transformer-based models. The latter part of the course applies these models to various NLP tasks, exploring relevant datasets, evaluation metrics, use cases, and delving into both realistic and open research questions.