ETHZ++ NLP Reading Group

Time: Fri 15-16h via Zoom

Reading List

Date	Presenter(s)	Topic	Title	Authors
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