Schedule

Plan Materials Resources Assignments
Mar 28
  1. Lecture: Chris Potts (in person and on Zoom)
  1. Video: Course overview [slides]
  2. Notebook: Course set-up
  3. Notebook: Jupyter notebook tutorial
  4. Notebook: NumPy tutorial
  5. Notebook: PyTorch tutorial
  1. Levesque 2013
  2. Manning 2015
  3. Potts 2019
  4. Video: The challenge and promise of artificial intelligence
  5. Podcast: The ELIZA effect (99% Invisible)
Vector space models
Mar 30
  1. Working session (team available in person and on Zoom)
  1. Video: High-level goals and guiding hypotheses [slides]
  2. Video: Matrix designs [slides]
  3. Video: Vector comparison [slides]
  4. Video: Basic reweighting [slides]
  5. Notebook: Designs, distances, basic reweighting
  6. Video: Dimensionality reduction [slides]
  7. Notebook: Dimensionality reduction and representation learning
  8. Video: Retrofitting [slides]
  9. Notebook: Retrofitting
  10. Video: Static representations from contextual models [slides]
  11. Notebook: Static representations from contextual models
  1. Turney and Pantel 2010
  2. Smith 2019
  3. Mikolov et al. 2013
  4. Pennington et al. 2014
  5. Faruqui et al. 2015
  6. Bommasani et al. 2020
  1. Word relatedness assignment and bakeoff: due Apr  11, 3:15 pm Pacific [overview video]
  2. Quiz on course policies: due Apr  11, 3:15 pm Pacific
  3. Quiz 1: due Apr  11, 3:15 pm Pacific
Apr 4
Apr 6
Supervised sentiment analysis
Apr 11
  1. Special event: Conversation with Rishi Bommasani
  1. Video: Overview of supervised sentiment analysis [slides]
  2. Video: General practical tips [slides]
  3. Video: Stanford Sentiment Treebank [slides]
  4. Notebook: Overview of the Stanford Sentiment Treebank
  5. Video: DynaSent [slides]
  6. Video: sst.py [slides]
  7. Video: Hyperparameter search and classifier comparison [slides]
  8. Video: Feature representation [slides]
  9. Notebook: Hand-built feature functions
  10. Video: RNN classifiers [slides]
  11. Notebook: Dense feature representations and neural networks
  12. Video: Overview of contextual representation models [slides]
  13. Video: Transformers [slides]
  14. Video: BERT [slides]
  15. Video: RoBERTa [slides]
  16. Video: ELECTRA [slides]
  17. Video: Practical fine-tuning [slides]
  18. Notebook: Fine-tuning large language models
  1. Pang and Lee 2008
  2. Socher et al. 2013
  3. Goldberg 2015
  4. Tutorial videos on supervised learning
  5. Stanford AI Lab Deep Learning Tutorial
  6. McCann et al. 2017
  7. Peters et al. 2018
  8. Vaswani et al. 2017
  9. Devlin et al. 2018
  10. Liu et al. 2019
  11. Yang, Dai, et al. 2019
  12. Clark et al. 2019
  1. Supervised sentiment assignment and bakeoff: due Apr 20, 3:15 pm Pacific [overview video]
  2. Quiz 2: due Apr 20, 3:15 pm Pacific
Apr 13
Apr 18
  1. Special event: Conversation with Douwe Kiela
Grounded language understanding; OpenQA with retrieval
Apr 20
  1. Special event: Conversation with Adina Williams (on Zoom)
  1. Video: Overview of grounded language understanding [slides]
  2. Video: Speakers [slides]
  3. Video: Listeners [slides]
  4. Video: Varieties of contextual grounding [slides]
  5. Video: The Rational Speech Acts model [slides]
  6. Video: Neural RSA [slides]
  7. Notebook: Pragmatic color describers
  8. Video: Overview of NLU and Information Retrieval [slides]
  9. Video: Classical IR [slides]
  10. Video: Neural IR, part 1 [slides]
  11. Video: Neural IR, part 2 [slides]
  12. Video: Neural IR, part 3 [slides]
  1. Lewis et al. 2017
  2. Golland et al. 2010
  3. Andreas and Klein 2016
  4. Monroe et al. 2017
  5. Tellex, Knepper, et al. 2014
  6. Vogel et al. 2014
  7. Brown et al. 2020
  8. Gao et al. 2020
  9. Khattab and Zaharia 2020
  10. Khattab et al. 2021
  1. Color reference assignment and bakeoff [overview video]
    OR
    Few-shot OpenQA with retrieval assignment and bakeoff [Colab copy; Github copy; overview video]: due May 2, 3:15 pm Pacific
  2. Quiz 3: due May 2, 3:15 pm Pacific
Apr 25
  1. Special event: Conversation with Omar Khattab (on Zoom)
Apr 27
Analysis methods
May 2
  1. Special event: Conversation with Richard Socher (on Zoom)
  1. Video: Overview of methods and metrics [slides]
  2. Video: Classifier metrics [slides]
  3. Video: Natural language generation metrics [slides]
  4. Notebook: Evaluation metrics
  5. Video: Data organization [slides]
  6. Video: Model evaluation [slides]
  7. Notebook: Evaluation methods
  8. Video: Overview of analysis methods in NLP [slides]
  9. Video: Adversarial testing [slides]
  10. Video: Adversarial training (and testing) [slides]
  11. Video: Probing [slides]
  12. Video: Feature attribution [slides]
  13. Video: Causal abstraction [slides]
  14. Notebook: Interchange Intervention Training: Equality learning tasks
  15. Video: Overview of Natural Language Inference [slides]
  16. Video: SNLI, MultiNLI, and Adversarial NLI [slides]
  17. Notebook: Tasks and datasets
  18. Video: Dataset artifacts and adversarial testing [slides]
  19. Video: Modeling strategies [slides]
  20. Notebook: NLI models
  21. Video: Attention [slides]
  1. Resnik and Lin 2010
  2. Smith 2011, Appendix B
  3. Dagan et al. 2006
  4. MacCartney and Manning 2008
  5. Bowman et al. 2015a
  6. Bowman et al. 2015b
  7. Rocktäschel et al. 2015
  8. Williams et al. 2018
  9. Nie et al. 2019
  10. Jia and Liang 2017
  11. Glockner et al. 2018
  12. Liu et al. 2019
  13. Naik et al. 2019
  1. Lit review: due May 11, 3:15 pm Pacific
  2. Quiz 4: due May 23, 3:15 pm Pacific
May 4
May 9
  1. Special event: Conversation with Ellie Pavlick (on Zoom)
May 11
  1. Experimental protocol: due May 23, 3:15 pm Pacific
May 16
  1. Special event: Conversation with Yulia Tsvetkov (on Zoom)
May 18
Writing up and presenting your work
May 23
  1. Special event: Conversation with Kalika Bali (on Zoom; special time 8:00 pm Pacific)
  1. Presenting your work: Your final papers [slides]
  2. Writing NLP papers [slides]
  3. NLP conference submissions [slides]
  4. Giving talks [slides]
  1. Jason Eisner's Advice for Research Students
  2. Stuart Shieber on reporting research results
  3. David Goss on math style
  4. Novelist Cormac McCarthy’s tips on how to write a great science paper
  5. Geoff Pullum's Five Golden Rules (well, actually six) for giving academic presentations
  6. Patrick Blackburn: How to give a good talk
  1. Final paper: due June 7, 6:30 pm Pacific (end of our scheduled exam time, which we will not use)
May 25
May 30
  1. Memorial Day (no class)
Jun 1