Schedule

Date Paper Presenters
1/5 Introductions, Logistics
1/10 Introductory lecture
1/12 Sparse, Dense, and Attentional Representations for Text Retrieval Bhuwan & Sam
1/17 MLK Jr. Day; no class
1/19 Nearest Neighbor Machine Translation Group 1
1/24 Learning with Instance Bundles for Reading Comprehension Group 2
1/26 Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge Group 3
1/31 FNet: Mixing Tokens with Fourier Transforms Group 1
2/2 When Attention Meets Fast Recurrence: Training Language Models … Group 2
2/7 DEMix Layers: Disentangling Domains for Modular Language Modeling Group 3
2/9 Bad Characters: Imperceptible NLP Attacks Group 1
2/14 Distributionally Robust Language Modeling Group 2
2/16 Counterfactual Invariance to Spurious Correlations in Text Classification Group 3
2/21 Achieving Model Robustness through Discrete Adversarial Training Group 1
2/23 Learning to Recombine and Resample Data for Compositional … Group 2
2/28 Active Learning by Acquiring Contrastive Examples Group 3
3/2 Neural Data Augmentation via Example Extrapolation Group 1
3/7 & 3/9 Spring break; no class
3/14 Counterfactual Data Augmentation for Neural Machine Translation Group 2
3/16 Learning to Faithfully Rationalize by Construction Group 3
3/21 Measuring Association Between Labels and Free-Text Rationales Group 1
3/23 Aligning Faithful Interpretations with their Social Attribution Group 2
3/28 FastIF: Scalable Influence Functions for Efficient Model Group 3
3/30 QED: A Framework and Dataset for Explanations in Question Answering Group 1
4/4 Memorizing Transformers Group 2
4/6 LM-Critic: Language Models for Unsupervised Grammatical Error Correction Group 3
4/11 Presentations TBD
4/13 Presentations TBD