Hongyin Luo
Research Scientist - Computational
      
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32-G440Hongyin completed his Ph.D. at MIT EECS in May 2022, working on self-training for natural language processing. Now he is a postdoctoral associate at the spoken language systems group (SLS) of MIT CSAIL. His research interests focus on natural language processing. In detail, he is interested in exploring semantic representation models that help computers understand and generate natural languages better. He has been working on interpretable word representation learning, deep neural networks, co-reference resolution, and other NLP applications.
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Last updated Oct 17 '24
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Publications
Luo, Hongyin and Li, Shang-Wen and Yu, Seunghak and Glass, James
      
      
            Cooperative Learning of Zero-Shot Machine Reading Comprehension
      
      
            arXiv preprint arXiv:2103.07449, 2021
      
              
            Luo, Hongyin and Jiang, Lan and Belinkov, Yonatan and Glass, James
      
      
            Improving Neural Language Models by Segmenting, Attending, and Predicting the Future
      
      
            Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL) 2019
      
              
            Luo, Hongyin and Glass, Jim
      
      
            Learning Word Representations with Cross-Sentence Dependency for End-to-End Co-reference Resolution
      
      
            Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
      
              
            Fu, Jie and Luo, Hongyin and Feng, Jiashi and Low, Kian Hsiang and Chua, Tat-Seng
      
      
            Drmad: Distilling reverse-mode automatic differentiation for optimizing hyperparameters of deep neural networks
      
      
            arXiv preprint arXiv:1601.00917, 2016
      
              
            Luo, Hongyin and Liu, Zhiyuan and Luan, Huanbo and Sun, Maosong
      
      
            Online learning of interpretable word embeddings
      
      
            Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
      
              
            Luo, Hongyin and Li, Shang-Wen and Glass, James
      
      
            Prototypical Q Networks for Automatic Conversational Diagnosis and Few-Shot New Disease Adaption
      
      
            Interspeech 2020, 2020
      
              
            Luo, Hongyin and Glass, James and Lalwani, Garima and Zhang, Yi and Li, Shang-Wen
      
      
            Joint Retrieval-Extraction Training for Evidence-Aware Dialog Response Selection
      
      
            Proc. Interspeech 2021, 2021
      
              
             
 
 
  