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Box Embeddings: An open-source library for representation learning using geometric structures

Sep 10, 2021
Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum

* The source code and the usage and API documentation for the library is available at and 

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Word2Box: Learning Word Representation Using Box Embeddings

Jun 28, 2021
Shib Sankar Dasgupta, Michael Boratko, Shriya Atmakuri, Xiang Lorraine Li, Dhruvesh Patel, Andrew McCallum

* Work in progress 

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Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning

Apr 09, 2021
Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum

* NAACL-HLT 2021 

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Modeling Fine-Grained Entity Types with Box Embeddings

Jan 02, 2021
Yasumasa Onoe, Michael Boratko, Greg Durrett

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Improving Local Identifiability in Probabilistic Box Embeddings

Oct 29, 2020
Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Lorraine Li, Andrew McCallum

* Accepted at NeurIPS2020 

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ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning

May 02, 2020
Michael Boratko, Xiang Lorraine Li, Rajarshi Das, Tim O'Gorman, Dan Le, Andrew McCallum

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A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset

Jun 01, 2018
Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue-Nkoutche, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock

* Presented at the Machine Reading for Question Answering (MRQA 2018) Workshop at the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2018). 11 pages, 5 tables, 4 figures 

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