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CMU Advanced NLP: Document-Level Modeling

Graham Neubig via YouTube

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Overview

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This advanced lecture examines neural methods for modeling long documents, including long-sequence feature extraction, language modeling, coreference, and discourse parsing. It covers recurrent networks and several transformer-based approaches.

Syllabus

Intro
Documentlevel Language Modeling
Recurrent Neural Networks
Encoding Methods
Self Attendance
Transformer Excel
Compressive Transformer
Sparse Transformer
Adaptive Span Transformer
Sparse Computations
Reformer
Low Rank Approximation
Evaluation
Entity Coreference
Mention Detection
Components
Instances
Pair Models
Coreference
Coreference model
Coreference models
Discourse parsing
Neural models

Taught by

Graham Neubig

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