MIT 6.S191: Deep CPCFG for Information Extraction @AAmini

Uploaded April 2021 | Updated September 2026, 2 weeks ago

MIT Introduction to Deep Learning 6.S191: Lecture 9
Deep CPCFG for Information Extraction
Lecturer: Nigel Duffy and Freddy Chua, Ernst & Young AI Labs
January 2021

For all lectures, slides, and lab materials: http://introtodeeplearning.com
More details on Deep Conditional Probabilistic Context Free Grammars (CPCFG): arxiv.org/abs/2103.05908
Code and datasets: github.com/deepcpcfg/datasets

Lecture Outline
0:00 - Introduction
4:18 - What is information extraction?
7:19 - Types of information (headers, line items, etc)
11:57 - Representing document schemas
12:35 - Philosophy of end-to-end deep learning
16:38 - Context free grammars (CFG)
20:55 - Parsing with deep learning
27:10 - Learning objective and training
28:21 - 2 dimensional parsing
33:20 - Handling noise in the parsing
35:23 - Experimental results
38:00 - Question and answering

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