Preprints

• Rethinking with Retrieval: Faithful Large Language Model Inference
  Hangfeng He, Hongming Zhang, and Dan Roth
  In Arxiv 2023. [pdf] [code]

• A Law of Data Separation in Deep Learning
  Hangfeng He and Weijie Su
  In Arxiv 2022. [pdf] [code]

• Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic
  Matteo Sordello, Hangfeng He, and Weijie Su
  In Arxiv 2019. [pdf]

Publications

2023

• Transfer Learning via Representation Learning
  Mohammad Rostami, Hangfeng He, Muhao Chen, and Dan Roth
  In Federated and Transfer Learning (Book Chapter). [pdf]

2022

• Weighted Training for Cross-Task Learning
  Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, and Weijie Su (alphabetical order)
  In ICLR 2022 (oral presentation). [pdf] [code]

2021

• Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
  Cong Fang, Hangfeng He, Qi Long, and Weijie Su (alphabetical order)
  In PNAS 2021 (direct submission). [pdf] [code]

• Foreseeing the Benefits of Incidental Supervision
  Hangfeng He, Mingyuan Zhang, Qiang Ning, and Dan Roth
  In EMNLP 2021. [pdf] [code]

• Toward Better Generalization Bounds with Locally Elastic Stability
  Zhun Deng, Hangfeng He, and Weijie Su
  In ICML 2021. [pdf]

2020

• QANom: Question-Answer driven SRL for Nominalizations
  Ayal Klein, Jonathan Mamou, Valentina Pyatkin, Daniela Brook Weiss, Hangfeng He, Dan Roth, Luke Zettlemoyer, and Ido Dagan
  In COLING 2020. [pdf]

• Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity
  Shuxiao Chen, Hangfeng He, and Weijie Su (alphabetical order)
  In NeurIPS 2020. [pdf] [code]

• Towards Understanding the Dynamics of the First-Order Adversaries
  Zhun Deng, Hangfeng He, Jiaoyang Huang, and Weijie Su
  In ICML 2020. [pdf]

• QuASE: Question-Answer Driven Sentence Encoding
  Hangfeng He, Qiang Ning, and Dan Roth
  In ACL 2020. [pdf] [code] [demo]

• Understanding Spatial Relations through Multiple Modalities
  Soham Dan, Hangfeng He, and Dan Roth
  In LREC 2020 (short papers). [pdf]

• The Local Elasticity of Neural Networks
  Hangfeng He and Weijie Su
  In ICLR 2020. [pdf] [code]

2019

• Partial or Complete, That’s The Question
  Qiang Ning, Hangfeng He, Chuchu Fan, and Dan Roth
  In NAACL-HLT 2019. [pdf]

2018

• Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media: A Unified Model
  Jingjing Xu, Hangfeng He, Xu Sun, Xuancheng Ren, and Sujian Li
  In TASLP 2018. [pdf]

2017

• Detecting negation scope is easy, except when it isn’t
  Federico Fancellu, Adam Lopez, Bonnie Webber, and Hangfeng He
  In EACL 2017 (short papers). [pdf]

• F-Score Driven Max Margin Neural Network for Named Entity Recognition in Chinese Social Media
  Hangfeng He and Xu Sun
  In EACL 2017 (short papers). [pdf]

• A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media
  Hangfeng He and Xu Sun
  In AAAI 2017. [pdf]