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Scalable Bottom-Up Hierarchical Clustering

Nov 04, 2020
Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gokhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu

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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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Clustering-based Inference for Zero-Shot Biomedical Entity Linking

Oct 21, 2020
Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum

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Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion

Oct 09, 2020
Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum

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Unsupervised Pre-training for Biomedical Question Answering

Sep 27, 2020
Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate

* To appear in BioASQ workshop 2020 

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Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models

Sep 20, 2020
Subhajit Naskar, Amirmohammad Rooshenas, Simeng Sun, Mohit Iyyer, Andrew McCallum

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Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks

Sep 17, 2020
Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum

* To appear in EMNLP 2020 

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A Simple Approach to Case-Based Reasoning in Knowledge Bases

Jun 25, 2020
Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum

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AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Jun 24, 2020
Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han

* KDD 2020 

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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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Compact Representation of Uncertainty in Hierarchical Clustering

Feb 26, 2020
Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Ji-Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum

* 21 pages, 5 figures 

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Scalable Hierarchical Clustering with Tree Grafting

Dec 31, 2019
Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael Glass, Andrew McCallum

* 23 pages (appendix included), published at KDD 2019 

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Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision

Dec 02, 2019
Trapit Bansal, Pat Verga, Neha Choudhary, Andrew McCallum

* Accepted in AAAI 2020 

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Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition

Nov 17, 2019
Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum

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Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

Nov 10, 2019
Trapit Bansal, Rishikesh Jha, Andrew McCallum

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Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering

Sep 17, 2019
Ameya Godbole, Dilip Kavarthapu, Rajarshi Das, Zhiyu Gong, Abhishek Singhal, Hamed Zamani, Mo Yu, Tian Gao, Xiaoxiao Guo, Manzil Zaheer, Andrew McCallum

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Optimal Transport-based Alignment of Learned Character Representations for String Similarity

Jul 23, 2019
Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum

* ACL Long Paper 

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Supervised Hierarchical Clustering with Exponential Linkage

Jun 19, 2019
Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum

* Appears in ICML 2019 

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Energy and Policy Considerations for Deep Learning in NLP

Jun 05, 2019
Emma Strubell, Ananya Ganesh, Andrew McCallum

* In the 57th Annual Meeting of the Association for Computational Linguistics (ACL). Florence, Italy. July 2019 

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The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

May 16, 2019
Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, Elsa Olivetti

* Accepted as a long paper at the Linguistic Annotation Workshop (LAW) at ACL 2019 

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Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering

May 14, 2019
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum

* Published at ICLR 2019 

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OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference

Apr 12, 2019
Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum

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Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders

Apr 04, 2019
Andrew Drozdov, Pat Verga, Mohit Yadav, Mohit Iyyer, Andrew McCallum

* 14 pages, 8 figures, 8 tables. NAACL 2019 

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Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

Dec 31, 2018
Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa Olivetti

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Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks

Dec 22, 2018
Amirmohammad Rooshenas, Dongxu Zhang, Gopal Sharma, Andrew McCallum

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Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?

Nov 12, 2018
Emma Strubell, Andrew McCallum

* In Proceedings of the Workshop on the Relevance of Linguistic Structure in Neural Architectures for NLP, ACL 2018 

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Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension

Oct 12, 2018
Rajarshi Das, Tsendsuren Munkhdalai, Xingdi Yuan, Adam Trischler, Andrew McCallum

* ICLR 2019 submission 

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Embedded-State Latent Conditional Random Fields for Sequence Labeling

Sep 28, 2018
Dung Thai, Sree Harsha Ramesh, Shikhar Murty, Luke Vilnis, Andrew McCallum

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