I am a PhD student in Computer Science at the University of Texas at Austin, advised by Greg Durrett and Eunsol Choi. I am interested in developing intelligent systems modeling or replicating human intelligence. My research interests focus on natural language processing and machine learning, particularly in deep learning approaches for natural language understanding problems.
Before coming to Austin, I completed my master’s degree in Data Science at New York University. Prior to that I received my bachelor’s degree from Baruch College.
Interests. Natural Language Processing, Machine Learning
Publications
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Entity Cloze By Date: What LMs Know About Unseen Entities,
NAACL 2022 Findings.
Yasumasa Onoe, Michael J.Q. Zhang, Eunsol Choi, and Greg Durrett
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Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection,
MUWS Workshop at WWW 2022.
Diego Garcia-Olano, Yasumasa Onoe, and Joydeep Ghosh
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Cross-Lingual Fine-Grained Entity Typing,
arXiv 2021.
Nila Selvaraj, Yasumasa Onoe, and Greg Durrett
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CREAK: A Dataset for Commonsense Reasoning over Entity Knowledge,
NeurIPS 2021 Datasets and Benchmarks Track.
Yasumasa Onoe, Michael J.Q. Zhang, Eunsol Choi, and Greg Durrett
[code]
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Modeling Fine-Grained Entity Types with Box Embeddings,
ACL 2021.
Yasumasa Onoe, Michael Boratko, Andrew McCallum, and Greg Durrett
[code]
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Biomedical Interpretable Entity Representations,
ACL 2021 Findings.
Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron Wallace and Kush Varzney
[code]
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Interpretable Entity Representations through Large-Scale Typing,
EMNLP 2020 Findings.
Yasumasa Onoe and Greg Durrett
[code]
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Fine-Grained Entity Typing for Domain Independent Entity Linking,
AAAI 2020.
Yasumasa Onoe and Greg Durrett
[code]
[poster]
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Learning to Denoise Distantly-Labeled Data for Entity Typing,
NAACL 2019.
Yasumasa Onoe and Greg Durrett
[code]
[poster]
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Gated Word-Character Recurrent Language Model,
EMNLP 2016.
Yasumasa Miyamoto (Onoe) and Kyunghyun Cho
[code]