Michael Boratko

According to our database, Michael Boratko authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Gecko: Versatile Text Embeddings Distilled from Large Language Models.

Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R. Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, Yi Luan, Sai Meher Karthik Duddu, Gustavo Hernández Ábrego, Weiqiang Shi, Nithi Gupta, Aditya Kusupati, Prateek Jain, Siddhartha Reddy Jonnalagadda, Ming-Wei Chang, Iftekhar Naim

CoRR, 2024

2022

Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings.

Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Modeling Label Space Interactions in Multi-label Classification using Box Embeddings.

Dhruvesh Patel, Pavitra Dangati, Jay-Yoon Lee, Michael Boratko, Andrew McCallum

Proceedings of the Tenth International Conference on Learning Representations, 2022

Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings.

Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra, Shriya Atmakuri, Dhruvesh Patel, Xiang Li, Andrew McCallum

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity.

Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Word2Box: Learning Word Representation Using Box Embeddings.

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

CoRR, 2021

Modeling Fine-Grained Entity Types with Box Embeddings.

Yasumasa Onoe, Michael Boratko, Greg Durrett

CoRR, 2021

Min/max stability and box distributions.

Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, Andrew McCallum

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Box-To-Box Transformations for Modeling Joint Hierarchies.

Shib Sankar Dasgupta, Xiang Lorraine Li, Michael Boratko, Dongxu Zhang, Andrew McCallum

Proceedings of the 6th Workshop on Representation Learning for NLP, 2021

Capacity and Bias of Learned Geometric Embeddings for Directed Graphs.

Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning.

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

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

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

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

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2021

Modeling Fine-Grained Entity Types with Box Embeddings.

Yasumasa Onoe, Michael Boratko, Andrew McCallum, Greg Durrett

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Improving Local Identifiability in Probabilistic Box Embeddings.

Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Li, Andrew McCallum

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Michael Boratko, Xiang Li, Tim O'Gorman, Rajarshi Das, Dan Le, Andrew McCallum

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Representing Joint Hierarchies with Box Embeddings.

Dhruvesh Patel, Shib Sankar Dasgupta, Michael Boratko, Xiang Li, Luke Vilnis, Andrew McCallum

Proceedings of the Conference on Automated Knowledge Base Construction, 2020

2019

Smoothing the Geometry of Probabilistic Box Embeddings.

Xiang Li, Luke Vilnis, Dongxu Zhang, Michael Boratko, Andrew McCallum

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

An Interface for Annotating Science Questions.

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

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018

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

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

Proceedings of the Workshop on Machine Reading for Question Answering@ACL 2018, 2018