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Advanced NLP 2022: Modeling Long Sequences

Graham Neubig via YouTube

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Overview

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This advanced lecture covers methods for modeling long sequences in NLP, including self-attention, Transformer-XL, Compressive, Sparse, Adaptive Span, Sparse Span, and Reformer models. It also addresses feature extraction, document processing tasks, and coreference model components.

Syllabus

Introduction
NLP Tasks
Modeling Long Sequences
Separate Encoding
Selfattention Transformers
Transformer XL
Compressive Transformers
Sparse Transformers
Adaptive Span Transformers
Sparse Span Transformers
Reformer Model
Low Rank Approximation
Sparse Attention
Evaluation
Other Methods
Questions
Components of Coreference Models
Mention Pair Models
Model

Taught by

Graham Neubig

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