Yichen Jiang (姜翌辰）

I'm a 2nd-year PhD student (7th-year Tar Heel) at Department of Computer Science at University of North Carolina at Chapel Hill, where I have spent the last 5 years pursuing my bachelor and master degree. I am advised by Prof. Mohit Bansal and work in UNC-NLP Research Group. My research focuses on Natural Language Processing and structured Deep Learning. In general, I build intuitive and interpretable Neural Network models to tackle some of the most challenging Natural Language Generation (NLG) (e.g., text summarization), and Natural Language Understanding (NLU) (e.g., machine reading-comprehension).

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Research

I'm interested in natural language processing, computer vision, multi-modal system, machine learning, statistics, optimization. My research interest centers on building interpretable neural networks that achieves state-of-the-art performace in tasks related to human language.

HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification
Yichen Jiang*, Shikha Bordia*, Zheng Zhong, Charles Dognin, Maneesh Singh, Mohit Bansal
Findings of EMNLP 2020
arxiv / data+code / bibtex
Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning
Yichen Jiang, Mohit Bansal
Proceedings of EMNLP 2019, Hong Kong, China
arxiv / code / bibtex
Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
Yichen Jiang, Mohit Bansal
Proceedings of ACL 2019, Florence, Italy
arxiv / code / slides / bibtex
Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
Yichen Jiang*, Nitish Joshi*, Yen-chun Chen, and Mohit Bansal
Proceedings of ACL 2019, Florence, Italy
arxiv / code / slides / bibtex
Closed-book Training to Improve Summarization Encoder Memory
Yichen Jiang, Mohit Bansal
Proceedings of EMNLP 2018, Brussels, Belgium
arxiv / poster / bibtex

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