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Augmenting Scientific Creativity with Retrieval across Knowledge Domains


Jun 02, 2022
Hyeonsu B. Kang, Sheshera Mysore, Kevin Huang, Haw-Shiuan Chang, Thorben Prein, Andrew McCallum, Aniket Kittur, Elsa Olivetti

* NLP+HCI Workshop at NAACL 2022 

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Inducing and Using Alignments for Transition-based AMR Parsing


May 03, 2022
Andrew Drozdov, Jiawei Zhou, Radu Florian, Andrew McCallum, Tahira Naseem, Yoon Kim, Ramon Fernandez Astudillo

* Accepted at NAACL 2022 

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CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases


Apr 18, 2022
Dung Thai, Srinivas Ravishankar, Ibrahim Abdelaziz, Mudit Chaudhary, Nandana Mihindukulasooriya, Tahira Naseem, Rajarshi Das, Pavan Kapanipathi, Achille Fokoue, Andrew McCallum

* 8 pages, 3 figurs, 4 tables 

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A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes


Apr 13, 2022
Dongxu Zhang, Sunil Mohan, Michaela Torkar, Andrew McCallum

* LREC 2022 (Oral) 

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Knowledge Base Question Answering by Case-based Reasoning over Subgraphs


Feb 22, 2022
Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Robin Jia, Manzil Zaheer, Hannaneh Hajishirzi, Andrew McCallum


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Sublinear Time Approximation of Text Similarity Matrices


Dec 17, 2021
Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco

* 25 pages, 10 figures 

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Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP


Nov 02, 2021
Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum

* To appear at EMNLP 2021 

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A Dataset for Discourse Structure in Peer Review Discussions


Oct 16, 2021
Neha Nayak Kennard, Tim O'Gorman, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Rajarshi Das, Hamed Zamani, Andrew McCallum


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Improved Latent Tree Induction with Distant Supervision via Span Constraints


Sep 10, 2021
Zhiyang Xu, Andrew Drozdov, Jay Yoon Lee, Tim O'Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, Andrew McCallum

* EMNLP 2021 

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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 https://github.com/iesl/box-embeddings and https://www.iesl.cs.umass.edu/box-embeddings/main/index.html 

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