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  • Sergi Castella i Sapé

EMNLP 2020: wrapping up.

Time to look back at a great conference and collect learnings. A brief reflection on our experience, along with some personal recommendations from the team members about our favourite papers.



Last week (Nov. 16–20) we, Zeta Alpha, attended the EMNLP 2020 conference as sponsors. In a previous blog post, we presented an overview on what the conference had to offer in 2020, diving into what topics were gaining traction and one should pay attention to. Now that the conference is behind us, here are some of our favorites.

Firstly, we found useful the fact that everybody attending was in front of a computer, which meant they could feel our product with their own eyes and fingers and it was great to see their enthusiasm about our product. However, attracting the eyeballs of the casual wanderer is far more challenging online than it is in a physical setting.

About the Content

All three main keynotes sparked interest and discussion among attendees: Claire Cardie’s talk on the big picture around Information Extraction, Rich Caruana on interpretable ML and Janet Pierrehumbert on Linguistic Behaviour and NLP. To us, Rich’s talk stood out as packed with valuable insight while being entertaining: “Why Friends Don’t Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning”. In this keynote, Rich walked us through trends on ML interpretability along with several illustrative examples on how some interpretable models can be engineered to make better predictions. This talk was also important because it spoke to a broader trend in the ML community: a growing interest in interpretability and an acknowledgement that this facet is key if models want to make the jump from research to production. In terms of workshops, one of the most exciting bits was our participation in the new Scholarly Document Processing Workshop, where we presented our work “A New Neural Search and Insights Platform for Navigating and Organizing AI Research”, in which we detail the workings of our platform for navigating AI Research.

Our personal Top 10

Finally, we want to share some recommendations from our team on the works presented at EMNLP. Here’s a selection of our favourite 10 in no particular order, followed by a short comment on what makes them special. This is a solid start if you missed the conference and want to catch up!


Our wrap-up comes to an end here, but our presence at conferences does not. Next up, we’ll be at NeurIPS in a couple of weeks, so make sure to catch up with us there! In the meanwhile, make sure to follow us on twitter @ZetaVector to not miss a thing.

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