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  • Department of Computer Science, University of Oxford
  • Oxford, United Kingdom
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MJ-Jang/README.md

M.J is a DPhil student in Computer Science at the University of Oxford supervised by professor Thomas Lukasiewicz. His current research focuses on investigating inconsistent behaviours of neural language models and developing remedies to alleviate the issues. M.J received a B.Sc degree in Industrial Management Engineering from Korea University in 2017. He earned an M.Eng degree in 2019 from the same affiliation and supervised by professor Pilsung Kang. M.J has previously worked for SK Telecom in Seoul, South Korea, as a natural language processing (NLP) scientist & engineer from 2019 to 2020.

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  1. Machine-Translation Machine-Translation Public

    Neural machine translation model(Encoder decoder model, Attention bidirectional model)

    Python 6

  2. Auto_encoder Auto_encoder Public

    Auto encoder models(Seq2Seq, VAE)

    Python 4 1

  3. RNN_SVAE RNN_SVAE Public

    RNN SVAE model

    Python 5 2

  4. Paraphrase-Thought Paraphrase-Thought Public

    Paraphrase Thought model

    Jupyter Notebook 6 2

  5. Hierachical_Ext_Summarization Hierachical_Ext_Summarization Public

    Hierarchical extractive summarization model using Transformer structure (Korean)

    Python 2 1

  6. beyond-distributional beyond-distributional Public

    Python 4