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 001; Achille Fokoue-Nkoutche; Pavan Kapanipathi; Nicholas Mattei; Ryan Musa; Kartik Talamadupula; et al. (QA@ACL, 2018)

An Interface for Annotating Science Questions. - Michael Boratko; Harshit Padigela; Divyendra Mikkilineni; Pritish Yuvraj; Rajarshi Das; Andrew McCallum; Maria Chang 001; Achille Fokoue; Pavan Kapanipathi; Nicholas Mattei; Ryan Musa; Kartik Talamadupula; et al. (EMNLP (Demonstration), 2018)

Smoothing the Geometry of Probabilistic Box Embeddings. - Xiang Li 069; Luke Vilnis; Dongxu Zhang; Michael Boratko; Andrew McCallum (ICLR, 2019)

Representing Joint Hierarchies with Box Embeddings. - Dhruvesh Patel; Shib Sankar Dasgupta; Michael Boratko; Xiang Li 069; Luke Vilnis; Andrew McCallum (AKBC, 2020)

ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. - Michael Boratko; Xiang Li 069; Tim O'Gorman; Rajarshi Das; Dan Le; Andrew McCallum (EMNLP (1), 2020)

Improving Local Identifiability in Probabilistic Box Embeddings. - Shib Sankar Dasgupta; Michael Boratko; Dongxu Zhang; Luke Vilnis; Xiang Li 069; Andrew McCallum (NeurIPS, 2020)

Modeling Fine-Grained Entity Types with Box Embeddings. - Yasumasa Onoe; Michael Boratko; Andrew McCallum; Greg Durrett (ACL/IJCNLP (1), 2021)

Box Embeddings: An open-source library for representation learning using geometric structures. - Tejas Chheda; Purujit Goyal; Trang Tran 005; Dhruvesh Patel; Michael Boratko; Shib Sankar Dasgupta; Andrew McCallum (EMNLP (Demos), 2021)

Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. - Xuelu Chen; Michael Boratko; Muhao Chen 001; Shib Sankar Dasgupta; Xiang Lorraine Li; Andrew McCallum (NAACL-HLT, 2021)

Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. - Michael Boratko; Dongxu Zhang; Nicholas Monath; Luke Vilnis; Kenneth L. Clarkson; Andrew McCallum (NeurIPS, 2021)

Box-To-Box Transformations for Modeling Joint Hierarchies. - Shib Sankar Dasgupta; Xiang Lorraine Li; Michael Boratko; Dongxu Zhang; Andrew McCallum (RepL4NLP@ACL-IJCNLP, 2021)

Min/max stability and box distributions. - Michael Boratko; Javier Burroni; Shib Sankar Dasgupta; Andrew McCallum (UAI, 2021)

Modeling Fine-Grained Entity Types with Box Embeddings. - Yasumasa Onoe; Michael Boratko; Greg Durrett (CoRR, 2021)

Word2Box: Learning Word Representation Using Box Embeddings. - Shib Sankar Dasgupta; Michael Boratko; Shriya Atmakuri; Xiang Lorraine Li; Dhruvesh Patel; Andrew McCallum (CoRR, 2021)

An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. - Siddhartha Mishra; Nicholas Monath; Michael Boratko; Ariel Kobren; Andrew McCallum (AAAI, 2022)

Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings. - Shib Sankar Dasgupta; Michael Boratko; Siddhartha Mishra; Shriya Atmakuri; Dhruvesh Patel; Xiang Li 069; Andrew McCallum (ACL (1), 2022)

Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. - Dhruvesh Patel; Pavitra Dangati; Jay-Yoon Lee; Michael Boratko; Andrew McCallum (ICLR, 2022)

Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. - Dongxu Zhang; Michael Boratko; Cameron Musco; Andrew McCallum (NeurIPS, 2022)

Every Answer Matters: Evaluating Commonsense with Probabilistic Measures. - Qi Cheng; Michael Boratko; Pranay Kumar Yelugam; Tim O'Gorman; Nalini Singh; Andrew McCallum; Xiang Li 069 (ACL (1), 2024)

A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. - Nicholas Monath; Will Sussman Grathwohl; Michael Boratko; Rob Fergus; Andrew McCallum; Manzil Zaheer (ICML, 2024)

Learning Representations for Hierarchies with Minimal Support. - Benjamin Rozonoyer; Michael Boratko; Dhruvesh Patel; Wenlong Zhao 001; Shib Sankar Dasgupta; Hung Le; Andrew McCallum (NeurIPS, 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 001; Michael Boratko; Rajvi Kapadia; Wen Ding; Yi Luan; Sai Meher Karthik Duddu; et al. (CoRR, 2024)

Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (CoRR, 2024)

LOFT: Scalable and More Realistic Long-Context Evaluation. - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (NAACL (Findings), 2025)

A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings. - Shib Sankar Dasgupta; Michael Boratko; Andrew McCallum (CoRR, 2025)

Gemini Embedding: Generalizable Embeddings from Gemini. - Jinhyuk Lee; Feiyang Chen; Sahil Dua; Daniel Cer; Madhuri Shanbhogue; Iftekhar Naim; Gustavo Hernández Ábrego; Zhe Li; Kaifeng Chen; Henrique Schechter Vera; Xiaoqi Ren; Shanfeng Zhang; et al. (CoRR, 2025)