NLP Highlights - podcast cover

NLP Highlights

Allen Institute for Artificial Intelligence•soundcloud.com
Science
**The podcast is currently on hiatus. For more active NLP content, check out the Holistic Intelligence Podcast linked below.** Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.
Last refreshed: ⓘ
Follow this podcast in the Metacast mobile app to refresh it and see new episodes.
Follow on
Apple Podcasts
Spotify
RSS
YouTube
Overcast
Pocket Casts
Episodes.fm
Download Metacast podcast app
Podcasts are better in Metacast mobile app
Don't just listen to podcasts. Learn from them with transcripts, summaries, and chapters for every episode. Skim, search, and bookmark insights. Learn more

Episodes

24 - Improving Hypernymy Detection with an Integrated Path-based and Distributional Method

ACL 2016 outstanding paper, by Vered Shwartz, Yoav Goldberg and Ido Dagan. Waleed presents this paper, discussing hypernymy detection and the methods used in the paper. It's pretty similar to work in relation extraction and knowledge base completion, so we also talk a bit about connections to other methods we're familiar with. Encoding paths using an RNN like they do (and like Arvind Neelakantan did for KBC) improves recall substantially, at the cost of some precision, which makes intuitive sens...

Jun 27, 2017•17 min

23 - Get To The Point: Summarization with Pointer-Generator Networks

ACL 2017 paper by Abigail See, Peter Liu, and Chris Manning. Matt presents the paper, describing the task (summarization on CNN/Daily Mail), the model (the standard copy + generate model that people are using these days, plus a nice coverage loss term), and the results (can't beat the extractive baseline, but coming close). It's a nice paper - very well written, interesting discussion section. https://www.semanticscholar.org/paper/Get-To-The-Point-Summarization-with-Pointer-Genera-See-Liu/13db67...

Jun 26, 2017•17 min

22 - Deep Multitask Learning for Semantic Dependency Parsing, with Noah Smith

An interview with Noah Smith. Noah tells us about his work with his students Hao Peng and Sam Thomson. We talk about what semantic dependency parsing is, the model that they used to approach the problem, how multi-task learning fits into this with a graph-based parser, and end with a little discussion about representation learning. https://www.semanticscholar.org/paper/Deep-Multitask-Learning-for-Semantic-Dependency-Pa-Peng-Thomson/406fd41b360bb02c0aaabff54055193fb5d9d7f1

Jun 16, 2017•31 min

21 - Contextual Explanation Networks, with Maruan Al-Shedivat

https://arxiv.org/abs/1705.10301 Maruan, Avinava Dubey and Eric Xing essentially put the post-hoc decision boundary explanations from the "Why Should I Trust You?" paper* as a core component of a predictive model. Maruan comes on to tell us about it. * https://www.semanticscholar.org/paper/Why-Should-I-Trust-You-Explaining-the-Predictions-Ribeiro-Singh/5636dca44384240ce9aff2b10b78458cd3c2f450

Jun 15, 2017•19 min

00 - Intro to the podcast

In this episode we briefly say what we're up to with the podcast. No technical content, just a description of what each episode will look like, and why we're doing this.

May 12, 2017•3 min
← Prev
For the best experience, listen in Metacast app for iOS or Android