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CMU Advanced NLP: Pre-training Methods

Graham Neubig via YouTube

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Overview

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This advanced NLP lecture examines pre-training methods, covering multi-task learning, sentence embeddings, BERT and its variants, and alternative language-modeling objectives. It also discusses sentence pair classification, semantic similarity, textual entailment, and masking.

Syllabus

Introduction
Neural Networks
Goals
Multitasking learning
Level of variety
Multitasking
Related Tasks
Multitask Learning
Pretraining
Pretraining Methods
Sentence Representations
Sentence Pair Classification
Sentence Pair Classification Examples
Semantic Similarity Relatedness
Textual entailment
Methods
Autoencoder
Skip thought vectors
Paraphrasebased contrastive learning
Largescale paraphrasing
Multitasking entailment
Supervised training
Sentence transformers
Context effect
Masking

Taught by

Graham Neubig

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