| Natural Language Generation with Vocabulary Constraints |
Swanson et al., 2014
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Generating sentence with word inclusion and vocab limits |
9/11/17 |
| Natural Language Processing with Python: Ch. 2 Accessing Text Corpora and Lexical Resources |
Bird, Klein, & Loper, 2009
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Textbook |
9/12/17 |
| Natural Language Processing with Python: Ch 3 Processing Raw Text |
Bird, Klein, & Loper, 2009
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Textbook |
9/12/17 |
| Speech and Language Processing: Ch. 15 Vector Semantics |
Jurafsky & Martin, 2017
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Textbook Draft |
9/14/17 |
| Speech and Language Processing: Ch. 16 Semantics with Dense Vectors |
Jurafsky & Martin, 2017
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Textbook Draft |
9/14/17 |
| Speech and Language Processing: Ch. 29 Dialog Systems and Chatbots |
Jurafsky & Martin, 2017
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Textbook Draft |
9/15/17 |
| Speech and Language Processing: Ch. 30 Advanced Dialog Systems |
Jurafsky & Martin, 2017
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Textbook Draft |
9/15/17 |
| Natural Language Processing with Python: Ch. 5 Categorizing and Tagging Words |
Bird, Klein, & Loper, 2009
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Textbook |
9/25/17 |
| Data-Driven Broad-Coverage Grammars for Opinionated Natural Language Generation (ONLG) |
Cagan et al., 2017
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Uses several PCFG models to generate a statement with a subject derived from topic modeling |
9/25/17 |
| Probabilistic Context-Free Grammars (PCFGs) |
Collins 2011
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Columbia NLP Course Notes: Intro to PCFGs |
9/25/17 |
| Speech and Language Processing: Ch. 12 Syntactic Parsing |
Jurafsky & Martin, 2017
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Textbook Draft |
10/17/17 |
| Speech and Language Processing: Ch. 11 Formal Grammars of English |
Jurafsky & Martin, 2017
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Textbook Draft |
10/19/17 |
| Speech and Language Processing: Ch. 13 Statistical Parsing |
Jurafsky & Martin, 2017
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Textbook Draft |
10/23/17 |
| Speech and Language Processing: Ch. 14 Dependency Parsing |
Jurafsky & Martin, 2017
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Textbook Draft |
10/23/17 |
| Speech and Language Processing: Ch. 4 Language Modeling with N-grams |
Jurafsky & Martin, 2017
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Textbook Draft |
10/23/17 |
| Speech and Language Processing: Ch. 9 Hidden Markov Models |
Jurafsky & Martin, 2017
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Textbook Draft |
10/24/17 |
| Speech and Language Processing: Ch. 22 Semantic Role Labeling |
Jurafsky & Martin, 2017
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Textbook Draft |
10/24/17 |
| Accurate Unlexicalized Parsing |
Klein & Manning, 2003
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Non-lexical improvements to the PCFG parsing model |
10/24/17 |
| Hierarchical Reinforcement Learning and Hidden Markov Models for Task-Oriented Natural Language Generation |
Dethlefs & Cuayáhuitl, 2011
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Using Hidden Markov Models for surface realization |
10/25/17 |
| Automatic Learning of Context-Free Grammar |
Chen, Tseng, & Chen, 2006
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Generating a CFG |
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| Learning to Understand Phrases by Embedding the Dictionary |
Hill et al., 2016
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| Adversarial Learning for Neural Dialogue Generation |
Li et al., 2017
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| Social media responses |
Cagan et al., 2014
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| Lexicalized Probabilistic Context-Free Grammars |
Collins 2011
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Columbia NLP Course Notes: Lexicalized PCFGs |
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| Tagging with Hidden Markov Models |
Collins 2011
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Columbia NLP Course Notes: HMMs |
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| Statistical Machine Translation: IBM Models 1 and 2 |
Collins 2011
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Columbia NLP Course Notes: Statistical Machine Translation |
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| Course Notes for COMS w4705: Language Modeling |
Collins 2011
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Columbia NLP Course Notes: Language Modeling |
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| CSE 322 - Introduction to Formal Methods in Computer Science: Chomsky Normal Form |
Bacon 2008
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University of Washington Formal Models Course Notes on Chomsky Normal Form |
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| Collective Semantic Role Labelling with Markov Logic |
Riedel & Meza-Ruiz, 2008
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