ETHZ++ NLP Reading Group

Time: Wed 12-13h Hybrid

Reading List

Date   Presenter(s) Topic Title Authors Bib  
15/01/20 Bashar Alhafni Gender-Aware Reinflection Gender-Aware Reinflection using Linguistically Enhanced Neural Models Bashar Alhafni, Nizar Habash, Houda Bouamor
11/12/19 Alessandro SpanBERT SpanBERT: Improving Pre-training by Representing and Predicting Spans Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, Omer Levy
04/12/19 Rowan Semantic Categories and Efficient Coding Semantic categories of artifacts and animals reflect efficient coding Noga Zaslavsky, Terry Regier, Naftali Tishby, Charles Kemp
27/11/19 Clara Mirror Descent Optimizing with constraints: reparametrization and geometry Vlad Niculae
6/11/19 Sankalan MC-Dropout Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Yarin Gal, Zoubin Ghahramani
30/10/19 Marinela Pruning The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle, Michael Carbin
23/10/19 Afra Sampling without Replacement Incremental Sampling Without Replacement for Sequence Models Kensen Shi, David Bieber, Charles Sutton
16/10/19 Shehzaad Critique of Leaderboards Utility is in the Eye of the User: A Critique of NLP Leaderboards Kawin Ethayarajh, Dan Jurafsky
9/10/19 Jiaoda Dropout and Pruning Learning Sparse Networks Using Targeted Dropout Aidan N. Gomez, Ivan Zhang, Siddhartha Rao Kamalakara, Divyam Madaan, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton
2/10/19 Tiago V-Information A Theory of Usable Information under Computational Constraints Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon
25/09/19 Tianyu Coreference Resolution End-to-end Neural Coreference Resolution Kenton Lee, Luheng He, Mike Lewis, Luke Zettlemoyer
18/09/19 Eleanor Centering Theory Centering: A Framework for Modeling the Local Coherence of Discourse Barbara J. Grosz, Aravind K. Joshi, Scott Weinstein
02/07/19 - 23/07/19 Reinforcement Learning Fundamentals of Reinforcement Learning Martha White and Adam White
01/05/19 Bayesian Non-Parametrics Bayesian density estimation and inference using mixtures
Markov chain sampling methods for Dirichlet process mixture models
28/04/19 NLP Retrospective Experience Grounds Language
Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data
24/04/19 Bayesian Non-Parametrics Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structures
17/04/19 Bayesian Non-Parametrics Lecture Notes on Bayesian Nonparametrics - Ch.6: Exchangeability
15/04/19 Probing Information-Theoretic Probing with Minimum Description Length
14/04/19 Bayesian Non-Parametrics Lecture Notes on Bayesian Nonparametrics - Ch.2: Clustering and the Dirichlet Process
Stat 362: Bayesian Nonparametrics - Lecture 1