Please move to LiLab Page for more recent publications.

Papers (peer-reviewed)

• Surfer100: Generating Surveys From Web Resources, Wikipedia-style
  Irene Li, Alexander Fabbri, Rina Kawamura, Yixin Liu, Xiangru Tang, Jaesung Tae, Chang Shen, Sally Ma, Tomoe Mizutani, Dragomir Radev
  LREC, 2022
• 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
  Computer Science Review, volume 46, 2022
• LiGCN: Label-interpretable Graph Convolutional Networks for Multi-label Text Classification
  Irene Li, Aosong Feng, Tianxiao Li, Hao Wu, Toyotaro Suzumura and Ruihai Dong
  DLG4NLP Workshop, NAACL 2022.
• Variational Graph Autoencoding as Cheap Supervision for AMR Coreference Resolution
  Irene Li, Linfeng Song, Kun Xu and Dong Yu
  ACL, 2022
• 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. 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)

• A Transfer Learning Pipeline for Educational Resource Discovery with Application in Leading Paragraph Generation
  Irene Li, Thomas George, Alexander Fabbri, Tammy Liao, Benjamin Chen, Rina Kawamura, Richard Zhou, Vanessa Yan, Swapnil Hingmire and Dragomir Radev
  2022

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

• AI Blueprints: How to build and deploy AI business projects
  Author: Dr Joshua Eckroth
  Translators: Xiaohu Zhu, Irene Li
  Chinese Version Link
• Learning TensorFlow: A Guide to Building Deep Learning Systems
  Authors: Itay Lieder, Yehezkel Resheff, Tom Hope
  Translators: Xiaohu Zhu, Irene Li
  Chinese Version Link