Papers (peer-reviewed)
- Improving Cross-lingual Text Classification with Zero-shot Instance-Weighting
Irene Li, Prithviraj Sen, Huaiyu Zhu, Yunyao Li and Dragomir Radev
RepL4NLP Workshop, ACL, 2021 - Unsupervised Cross-Domain Prerequisite Chain Learning using Variational Graph Autoencoders
Irene Li, Vanessa Yan, Tianxiao Li, Rihao Qu and Dragomir Radev
ACL short, 2021. Slide. Github. - R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning
Irene Li, Alexander Fabbri, Swapnil Hingmire, Dragomir Radev
COLING, 2020
Github - What are We Depressed about When We Talk about COVID19: Mental Health Analysis on Tweets Using Natural Language Processing
Irene Li, Yixin Li, Tianxiao Li, Sergio Alvarez-Napagao and Dario Garcia
Fortieth SGAI International Conference on Artificial Intelligence, 2020
Github - A Neural Topic-Attention Model for Medical Term Abbreviation Disambiguation
Irene Li, Michihiro Yasunaga, Muhammed Yavuz Nuzumlalı, Cesar Caraballo, Shiwani Mahajan, Harlan Krumholz and Dragomir Radev
Machine Learning for Health Workshop at NeurIPS 2019, Code - Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
Alexander Fabbri, Irene Li, Tianwei She, Suyi Li and Dragomir Radev
Proceedings of ACL 2019, Dataset and Code - What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning
Irene Li, Alexander Fabbri, Robert Tung, and Dragomir Radev
Proceedings of AAAI 2019, Dataset BLOG - TutorialBank: Using a Manually-Collected Corpus for Prerequisite Chains, Survey Extraction and Resource Recommendation
Alexander Fabbri, Irene Li, Prawat Trairatvorakul, Yijiao He, Weitai Ting, Robert Tung, Caitlin Westerfield and Dragomir Radev
Proceedings of ACL 2018 Dataset BLOG - SParC: Cross-Domain Semantic Parsing in Context
Tao Yu, Rui Zhang, Michihiro Yasunaga, Yi-Chern Tan, Xi Victoria Lin, Suyi Li, Heyang Er, Irene Li, Bo Pang, Tao Chen, Emily Ji, Shreya Dixit, David Proctor, Sungrok Shim, Jonathan Kraft, Vincent Zhang, Caiming Xiong, Richard Socher and Dragomir Radev
Proceedings of ACL 2019 - ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks
Michihiro Yasunaga, Jungo Kasai, Rui Zhang, Alexander Fabbri, Irene Li, Dan Friedman, and Dragomir Radev
Proceedings of AAAI 2019 - Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, Zilin Zhang, and Dragomir Radev
Proceedings of EMNLP 2018 BLOG - Medical Text Classification Using Convolutional Neural Networks
Mark Hughes, Irene Li, Spyros Kotoulas, Toyotaro Suzumura
Informatics for Health 2017
Papers (on arXiv)
- Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review
Irene Li, Jessica Pan, Jeremy Goldwasser, Neha Verma, Wai Pan Wong, Muhammed Yavuz Nuzumlalı, Benjamin Rosand, Yixin Li, Matthew Zhang, David Chang, R. Andrew Taylor, Harlan M. Krumholz and Dragomir Radev
2021 - Heterogeneous Graph Neural Networks for Multi-label Text Classification
Irene Li, Tianxiao Li, Yixin Li, Ruihai Dong and Toyotaro Suzumura
2020 summer work, submitted to arXiv in 2021
Papers (solo)
- Detecting Bias in Transfer Learning Approaches for Text Classification
Irene Li
A class research project done in 2019, submitted to arXiv in 2021
Book Translation
- Learning TensorFlow: A Guide to Building Deep Learning Systems
Authors: Itay Lieder, Yehezkel Resheff, Tom Hope
Translators: Xiaohu Zhu, Irene Li
Chinese Version Link
