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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Jan 01, 2021
Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih

* 26 pages 

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A Memory Efficient Baseline for Open Domain Question Answering

Dec 30, 2020
Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Sebastian Riedel, Edouard Grave


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Autoregressive Entity Retrieval

Oct 02, 2020
Nicola De Cao, Gautier Izacard, Sebastian Riedel, Fabio Petroni

* 18 pages, 6 figures, 8 tables 

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Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking

Oct 01, 2020
Michael Sejr Schlichtkrull, Nicola De Cao, Ivan Titov


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KILT: a Benchmark for Knowledge Intensive Language Tasks

Sep 04, 2020
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vassilis Plachouras, Tim Rocktäschel, Sebastian Riedel


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The Power Spherical distribution

Jun 15, 2020
Nicola De Cao, Wilker Aziz

* 8 pages, 2 figures, 1 table. Code at: https://github.com/nicola-decao/power_spherical 

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How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking

Apr 30, 2020
Nicola De Cao, Michael Schlichtkrull, Wilker Aziz, Ivan Titov

* 19 pages, 14 figures, 4 tables 

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Block Neural Autoregressive Flow

Apr 09, 2019
Nicola De Cao, Ivan Titov, Wilker Aziz

* 12 pages, 3 figures, 3 tables 

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Hyperspherical Variational Auto-Encoders

Sep 26, 2018
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, Jakub M. Tomczak

* Uncertainty in Artificial Intelligence (UAI). Proceedings of the Thirty-Fourth Conference (2018) 856- 865 
* GitHub repository: http://github.com/nicola-decao/s-vae-tf, Blogpost: https://nicola-decao.github.io/s-vae 

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Question Answering by Reasoning Across Documents with Graph Convolutional Networks

Aug 29, 2018
Nicola De Cao, Wilker Aziz, Ivan Titov

* 7 pages, 3 figures, 2 tables 

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Explorations in Homeomorphic Variational Auto-Encoding

Jul 12, 2018
Luca Falorsi, Pim de Haan, Tim R. Davidson, Nicola De Cao, Maurice Weiler, Patrick Forré, Taco S. Cohen

* 16 pages, 8 figures, ICML workshop on Theoretical Foundations and Applications of Deep Generative Models 

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MolGAN: An implicit generative model for small molecular graphs

May 30, 2018
Nicola De Cao, Thomas Kipf

* 11 pages, 3 figures, 3 tables 

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