56 - Deep contextualized word representations, with Matthew Peters
NAACL 2018 paper, by Matt Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Chris Clark, Kenton Lee, and Luke Zettlemoyer. In this episode, AI2's own Matt Peters comes on the show to talk about his re...
4 Apr 201830min
55 - Matchbox: Dispatch-driven autobatching for imperative deep learning, with James Bradbury
In this episode, we take a more systems-oriented approach to NLP, looking at issues with writing deep learning code for NLP models. As a lot of people have discovered over the last few years, efficie...
28 Mar 201831min
54 - Simulating Action Dynamics with Neural Process Networks, with Antoine Bosselut
ICLR 2018 paper, by Antoine Bosselut, Omer Levy, Ari Holtzman, Corin Ennis, Dieter Fox, and Yejin Choi. This is not your standard NLP task. This work tries to predict which entities change state ove...
26 Mar 201836min
53 - Classical Structured Prediction Losses for Sequence to Sequence Learning, with Sergey and Myle
NAACL 2018 paper, by Sergey Edunov, Myle Ott, Michael Auli, David Grangier, and Marc'Aurelio Ranzato, from Facebook AI Research In this episode we continue our theme from last episode on structured p...
21 Mar 201826min
52 - Sequence-to-Sequence Learning as Beam-Search Optimization, with Sam Wiseman
EMNLP 2016 paper by Sam Wiseman and Sasha Rush. In this episode we talk with Sam about a paper from a couple of years ago on bringing back some ideas from structured prediction into neural seq2seq mo...
15 Mar 201823min
51 - A Regularized Framework for Sparse and Structured Neural Attention, with Vlad Niculae
NIPS 2017 paper by Vlad Niculae and Mathieu Blondel. Vlad comes on to tell us about his paper. Attentions are often computed in neural networks using a softmax operator, which maps scalar outputs fr...
12 Mar 201816min
50 - Cardinal Virtues: Extracting Relation Cardinalities from Text, with Paramita Mirza
ACL 2017 paper, by Paramita Mirza, Simon Razniewski, Fariz Darari, and Gerhard Weikum. There's not a whole lot of work on numbers in NLP, and getting good information out of numbers expressed in text...
14 Feb 201827min
49 - A Joint Sequential and Relational Model for Frame-Semantic Parsing, with Bishan Yang
EMNLP 2017 paper by Bishan Yang and Tom Mitchell. Bishan tells us about her experiments on frame-semantic parsing / semantic role labeling, which is trying to recover the predicate-argument structure...
5 Feb 201826min
