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Bio:

Hi! I am Hai Ye (叶海). I am a Ph.D. candidate at the School of Computing, National University of Singapore (NUS), where I am working with prof. Hwee Tou Ng. I am supported by AISG Ph.D. Fellowship. I obtained my bachelor degree from Beihang University, Beijing, China.

Research:

My research is dedicated to building a robust NLP model capable of understanding and interacting with natural language on par with humans. Currently, my efforts are centered on enhancing the model's ability in dealing with unforeseen situations. A key aspect of this work is the active inclusion of human input, which serves to bolster the model's decision-making reliability and facilitate its continual improvement.

[A Collection of Language Model Alignment and Beyond]

Contact: hye.me [at] outlook [dot] com

Selected Papers [Full]

(* indicates equal contribution)

  • Multi-Source Test-Time Adaptation as Dueling Bandits for Extractive Question Answering
      Hai Ye, Qizhe Xie, Hwee Tou Ng
      In Proceedings of the Association for Computational Linguistic (ACL), 2023, Long paper.
      [paper]

  • Beware of Model Collapse! Fast and Stable Test-time Adaptation for Robust Question Answering
      Yi Su, Yixin Ji, Juntao Li, Hai Ye, Min Zhang
      In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023, Long paper.

  • Isotropic Representation Can Improve Zero-Shot Cross-Lingual Transfer on Multilingual Language Models
      Yixin Ji, Jikai Wang, Juntao Li, Hai Ye, Min Zhang
      In Findings of the Association for Computational Linguistics: EMNLP 2023 , Long paper.

  • Robust Question Answering against Distribution Shifts with Test-Time Adaptation: An Empirical Study
      Hai Ye, Yuyang Ding, Juntao Li, Hwee Tou Ng
      In Findings of the Association for Computational Linguistics: EMNLP 2022 , Long paper.
      [paper] [code]

  • On the Robustness of Question Rewriting Systems to Questions of Varying Hardness
      Hai Ye, Hwee Tou Ng, Wenjuan Han
      In Proceedings of the Association for Computational Linguistic (ACL), 2022, Long paper.
      [paper]

  • On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation
      Ruidan He*, Linlin Liu*, Hai Ye*, Qingyu Tan, Bosheng Ding, Liying Cheng, David Low, Lidong Bing, Luo Si
      In Proceedings of the Association for Computational Linguistic (ACL), 2021, Long paper.
      [paper]

  • Feature Adaptation of Pre-Trained Language Models across Languages and Domains with Robust Self-Training
      Hai Ye, Qingyu Tan, Ruidan He, Juntao Li, Hwee Tou Ng, Lidong Bing
      In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020, Long paper.
      [paper] [code]

  • Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model
      Juntao Li, Ruidan He, Hai Ye, Hwee Tou Ng, Lidong Bing, Rui Yan
       In Proceedings of International Joint Conferences on Artificial Intelligence (IJCAI), 2020.

  • Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization
      Hai Ye, Wenjie Li, Lu Wang
      In Proceedings of the Association for Computational Linguistic (ACL), 2019, Long paper.
      [paper] [poster]

  • Semi-Supervised Learning for Neural Keyphrase Generation
      Hai Ye, Lu Wang
      In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018, Long paper.
      [paper]

  • Interpretable Charge Predictions for Criminal Cases: Learning to Generate Court Views from Fact Descriptions
      Hai Ye*, Xin Jiang*, Zhunchen Luo*, Wenhan Chao
      In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics
     (NAACL), 2018, Long paper, Oral.
      [paper] [Data] [Slides]

  • Jointly Extracting Relations with Class Ties via Effective Deep Ranking
     Hai Ye, Wenhan Chao, Zhunchen Luo, Zhoujun Li
     In Proceedings of the Association for Computational Linguistic (ACL), 2017, Long paper.
     [paper] [code]

    Award

  • AISG PhD Fellowship
  • Research Achievement Award, SoC, NUS, 2022, 2023

    • Academic Services

  • Reviewer: ARR, ACL, NAACL, EMNLP, COLING

  • Volunteer: NAACL 2018

    • Last update: 2023