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Retrieving Complex Tables with Multi-Granular Graph Representation Learning


May 04, 2021
Fei Wang, Kexuan Sun, Muhao Chen, Jay Pujara, Pedro Szekely

* Accepted by SIGIR 2021 

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Probing Causal Common Sense in Dialogue Response Generation


Apr 21, 2021
Pei Zhou, Pegah Jandaghi, Bill Yuchen Lin, Justin Cho, Jay Pujara, Xiang Ren

* This article has been withdrawn by the authors. The submitted version was an early draft that has errors in the results which renders the analysis invalid 

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Representing Numbers in NLP: a Survey and a Vision


Mar 24, 2021
Avijit Thawani, Jay Pujara, Pedro A. Szekely, Filip Ilievski

* Accepted at NAACL 2021 

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Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources


Mar 21, 2021
Ninareh Mehrabi, Pei Zhou, Fred Morstatter, Jay Pujara, Xiang Ren, Aram Galstyan


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Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models


May 02, 2020
Pei Zhou, Rahul Khanna, Bill Yuchen Lin, Daniel Ho, Xiang Ren, Jay Pujara

* 15 pages, 11 figures. Work in progress 

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Human-like Time Series Summaries via Trend Utility Estimation


Jan 16, 2020
Pegah Jandaghi, Jay Pujara


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Using Noisy Extractions to Discover Causal Knowledge


Nov 16, 2017
Dhanya Sridhar, Jay Pujara, Lise Getoor


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Generic Statistical Relational Entity Resolution in Knowledge Graphs


Jul 04, 2016
Jay Pujara, Lise Getoor

* In the Sixth International Workshop on Statistical Relational AI, 2016 

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Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks


Jul 02, 2016
Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, Lise Getoor

* Presented at SIGKDD 12th International Workshop on Mining and Learning with Graphs (MLG'16) 

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