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2020 – today
- 2025
[c20]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, Panupong Pasupat, Aida Amini, Jeremy R. Cole, Sebastian Riedel, Iftekhar Naim, Ming-Wei Chang, Kelvin Guu:
LOFT: Scalable and More Realistic Long-Context Evaluation. NAACL (Findings) 2025: 6698-6723- [i15]Shib Sankar Dasgupta, Michael Boratko, Andrew McCallum:
A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings. CoRR abs/2502.10875 (2025) - [i14]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, Daniel Salz, Michael Boratko, Jay Han, Blair Chen, Shuo Huang, Vikram Rao, Paul Suganthan, Feng Han, Andreas Doumanoglou, Nithi Gupta, Fedor Moiseev, Cathy Yip, Aashi Jain, Simon Baumgartner, Shahrokh Shahi, Frank Palma Gomez, Sandeep Mariserla, Min Choi, Parashar Shah, Sonam Goenka, Ke Chen, Ye Xia, Koert Chen, Sai Meher Karthik Duddu, Yichang Chen, Trevor Walker, Wenlei Zhou, Rakesh Ghiya, Zach Gleicher, Karan Gill, Zhe Dong, Mojtaba Seyedhosseini, Yun-Hsuan Sung, Raphael Hoffmann, Tom Duerig:
Gemini Embedding: Generalizable Embeddings from Gemini. CoRR abs/2503.07891 (2025) - [i13]Orion Weller, Michael Boratko, Iftekhar Naim, Jinhyuk Lee:
On the Theoretical Limitations of Embedding-Based Retrieval. CoRR abs/2508.21038 (2025) - [i12]Henrique Schechter Vera, Sahil Dua, Biao Zhang, Daniel Salz, Ryan Mullins, Sindhu Raghuram Panyam, Sara Smoot, Iftekhar Naim, Joe Zou, Feiyang Chen, Daniel Cer, Alice Lisak, Min Choi, Lucas Gonzalez, Omar Sanseviero, Glenn Cameron, Ian Ballantyne, Kat Black, Kaifeng Chen, Weiyi Wang, Zhe Li, Gus Martins, Jinhyuk Lee, Mark Sherwood, Ju-yeong Ji, Renjie Wu, Jingxiao Zheng, Jyotinder Singh, Abheesht Sharma, Divyashree Sreepathihalli, Aashi Jain, Adham Elarabawy, AJ Co, Andreas Doumanoglou, Babak Samari, Ben Hora, Brian Potetz, Dahun Kim, Enrique Alfonseca, Fedor Moiseev, Feng Han, Frank Palma Gomez, Gustavo Hernández Ábrego, Hesen Zhang, Hui Hui, Jay Han, Karan Gill, Ke Chen, Koert Chen, Madhuri Shanbhogue, Michael Boratko, Paul Suganthan, Sai Meher Karthik Duddu, Sandeep Mariserla, Setareh Ariafar, Shanfeng Zhang, Shijie Zhang, Simon Baumgartner, Sonam Goenka, Steve Qiu, Tanmaya Dabral, Trevor Walker, Vikram Rao, Waleed Khawaja, Wenlei Zhou, Xiaoqi Ren, Ye Xia, Yichang Chen, Yi-Ting Chen, Zhe Dong, Zhongli Ding, Francesco Visin, Gaël Liu, Jiageng Zhang, Kathleen Kenealy, Michelle Casbon, Ravin Kumar, Thomas Mesnard, Zach Gleicher, Cormac Brick, Olivier Lacombe, Adam Roberts, Qin Yin, Yun-Hsuan Sung, Raphael Hoffmann, Tris Warkentin, Armand Joulin, Tom Duerig, Mojtaba Seyedhosseini:
EmbeddingGemma: Powerful and Lightweight Text Representations. CoRR abs/2509.20354 (2025) - 2024
- [c19]Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Li:
Every Answer Matters: Evaluating Commonsense with Probabilistic Measures. ACL (1) 2024: 493-506 - [c18]Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer:
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. ICML 2024 - [c17]Benjamin Rozonoyer, Michael Boratko, Dhruvesh Patel, Wenlong Zhao, Shib Sankar Dasgupta, Hung Le, Andrew McCallum:
Learning Representations for Hierarchies with Minimal Support. NeurIPS 2024 - [i11]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:
Gecko: Versatile Text Embeddings Distilled from Large Language Models. CoRR abs/2403.20327 (2024) - [i10]Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Lorraine Li:
Every Answer Matters: Evaluating Commonsense with Probabilistic Measures. CoRR abs/2406.04145 (2024) - [i9]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, Panupong Pasupat, Aida Amini, Jeremy R. Cole, Sebastian Riedel, Iftekhar Naim, Ming-Wei Chang, Kelvin Guu:
Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? CoRR abs/2406.13121 (2024) - [i8]Nicholas Monath, Will Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer:
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. CoRR abs/2409.01890 (2024) - 2022
- [c16]Siddhartha Mishra
, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum:
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. AAAI 2022: 7788-7796 - [c15]Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra, Shriya Atmakuri, Dhruvesh Patel, Xiang Li, Andrew McCallum:
Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings. ACL (1) 2022: 2263-2276 - [c14]Dhruvesh Patel, Pavitra Dangati, Jay-Yoon Lee, Michael Boratko, Andrew McCallum:
Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. ICLR 2022 - [c13]Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum:
Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. NeurIPS 2022 - 2021
- [c12]Yasumasa Onoe, Michael Boratko, Andrew McCallum, Greg Durrett:
Modeling Fine-Grained Entity Types with Box Embeddings. ACL/IJCNLP (1) 2021: 2051-2064 - [c11]Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum:
Box Embeddings: An open-source library for representation learning using geometric structures. EMNLP (Demos) 2021: 203-211 - [c10]Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum:
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. NAACL-HLT 2021: 882-893 - [c9]Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum:
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. NeurIPS 2021: 16423-16436 - [c8]Shib Sankar Dasgupta, Xiang Lorraine Li, Michael Boratko, Dongxu Zhang, Andrew McCallum:
Box-To-Box Transformations for Modeling Joint Hierarchies. RepL4NLP@ACL-IJCNLP 2021: 277-288 - [c7]Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, Andrew McCallum:
Min/max stability and box distributions. UAI 2021: 2146-2155 - [i7]Yasumasa Onoe, Michael Boratko, Greg Durrett:
Modeling Fine-Grained Entity Types with Box Embeddings. CoRR abs/2101.00345 (2021) - [i6]Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum:
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. CoRR abs/2104.04597 (2021) - [i5]Shib Sankar Dasgupta, Michael Boratko, Shriya Atmakuri, Xiang Lorraine Li, Dhruvesh Patel, Andrew McCallum:
Word2Box: Learning Word Representation Using Box Embeddings. CoRR abs/2106.14361 (2021) - [i4]Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum:
Box Embeddings: An open-source library for representation learning using geometric structures. CoRR abs/2109.04997 (2021) - 2020
- [c6]Dhruvesh Patel, Shib Sankar Dasgupta, Michael Boratko, Xiang Li, Luke Vilnis, Andrew McCallum:
Representing Joint Hierarchies with Box Embeddings. AKBC 2020 - [c5]Michael Boratko, Xiang Li, Tim O'Gorman, Rajarshi Das, Dan Le, Andrew McCallum:
ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. EMNLP (1) 2020: 1122-1136 - [c4]Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Li, Andrew McCallum:
Improving Local Identifiability in Probabilistic Box Embeddings. NeurIPS 2020 - [i3]Michael Boratko, Xiang Lorraine Li, Rajarshi Das, Tim O'Gorman, Dan Le, Andrew McCallum:
ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. CoRR abs/2005.00771 (2020) - [i2]Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Lorraine Li, Andrew McCallum:
Improving Local Identifiability in Probabilistic Box Embeddings. CoRR abs/2010.04831 (2020)
2010 – 2019
- 2019
- [c3]Xiang Li, Luke Vilnis, Dongxu Zhang, Michael Boratko, Andrew McCallum:
Smoothing the Geometry of Probabilistic Box Embeddings. ICLR 2019 - 2018
- [c2]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:
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. QA@ACL 2018: 60-70 - [c1]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:
An Interface for Annotating Science Questions. EMNLP (Demonstration) 2018: 102-107 - [i1]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:
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. CoRR abs/1806.00358 (2018)
Coauthor Index
aka: Xiang Lorraine Li
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last updated on 2025-10-19 21:53 CEST by the dblp team
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