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Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 12 - Question Answering

Chapters

0:0
0:18 Announcements
1:38 Dante Chen
2:53 What Is Question Answering
3:32 Open Domain Question Answering
3:49 What Is the Question Answering
11:20 Visual Question Answering
11:47 Part 2 Reading Comprehension
12:2 Reading Comprehension
14:27 Why Do We Care about the Reading Comprehension Problem
16:5 Information Extraction
16:50 Cementite Labeling
17:59 Stanford Question String Dataset
20:7 Stanford Question Three Data Sets
20:35 Evaluation
20:41 Evaluation Metrics
24:15 Build a Neural Models for Reading Comprehension
30:56 Character Embedding Layer
31:18 Word Embedding
33:57 Attention Flow Layer
71:50 The Reading Comprehension Model
75:3 Demo
85:9 Natural Questions
93:39 In What Extent Can in-Context Learning Help Models To Be More Robust with Respect to Different Domains
95:21 Future of Nlp

Transcript