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Schedule & Materials

Session Date Topics Assignments Reading List
  3/1 Holiday    
Lec 01 3/3 Intro to NLP, Math & ML Basics [slides]    
Lab 01 3/8 Math & ML Basics [slides][notebook]    
Lec 02 3/10 Text Classification, Recurrent Neural Networks [slides]   MNIST, [Socher et al., 2013], [Srivastava et al., 2014], [Mikolov et al., 2013]
Lab 02 3/15 Text Classification, Recurrent Neural Networks [slides][notebook]    
  3/17 Class canceled    
Lec 03 3/22 LSTM, Token Classification [slides] Assignment 1 is up Vanishing Gradients and Fancy RNNs, [Hochreiter & Schmidhuber, 1997]
Lab 03 3/24 LSTM, Token Classification [slides][notebook]    
Lec 04 3/29 Question Answering, Retrieval [slides]   [Rajpurkar et al., 2016], [Hermann et al., 2015], [Seo et al., 2017], [Chen et al., 2017], faiss, [Malkov & Yashunin, 2016]
Lab 04 3/31 Question Answering, Retrieval [slides] [notebook]    
Lec 05 4/5 Text Generation [slides] Assignment 1 is due (11pm KST) [Cho et al., 2014], [Bahdanau et al., 2015], [Luong et al., 2015]
Lab 05 4/7 Text Generation [slides] [notebook]    
Lec 06 4/12 Transformer [slides] Assignment 2 is up [Vaswani et al., 2017], Annotated Transformer
Lab 06 4/14 Transformer [slides] [notebook]    
  4/19 No class (midterm exam week)    
  4/21 No class (midterm exam week)    
  4/26 Class canceled Assignment 2 is due (11pm KST)  
Lec 07 4/28 Transformer (2) [slides]   [Ioffe & Szgedy 2015], [Ba et al., 2016], [Shaw et al., 2018]
Lab 07 5/3 Transformer (2) [slides] [notebook] Assignment 3 is up  
  5/5 No class (Holiday) Final Project Proposal is up (on KLMS)  
Lec 08 5/10 Language Model [slides] Final Project Proposal is due (11pm KST) [Min et al., 2017], [Peters et al., 2018], [Howard & Ruder, 2018], [Radford et al., 2018]
Lab 08 5/12 Language Model [slides] [notebook]    
Lec 09 5/17 BERT [slides] Assignment 3 is due (11pm KST) [Devlin et al., 2018], [Yang et al., 2019], [Liu et al., 2019], BERT Slides
Lab 09 5/19 BERT [notebook]   transformers Tutorial
Lec 10 5/24 T5 [slides] Assignment 4 is up [Lewis et al., 2020a], [Raffel et al., 2020], [Roberts et al., 2020], [Lewis et al., 2020b]
Lab 10 5/26 T5 [notebook]    
Lec 11 5/31 GPT-2, Few-Shot Learning [slides]   [Radford et al., 2019], Few-Shot Learning Tutorial
Lab 11 6/2 GPT-2, Few-Shot Learning [notebook]    
  6/7 Class canceled Assignment 4 and Final Project Report are due (11pm KST)  
Lec 12 6/9 Recent Trend in NLP, Final Project Presentations [slides]   [Kaplan et al., 2020], [Brown et al., 2020], [Ramesh et al., 2021]
  6/14 No class (final exam week)    
  6/16 No class (final exam week)