Youngwoo Kim

University of Massachusetts Amherst
youngwookim@cs.umass.edu

I am PhD student in University of Massachusetts Amherst (UMass) working with James Allan. I am working in Center for Intelligent Information Retrieval (CIIR). My research interests include various aspects of information retrieval (IR) and natural language processing (NLP).

I recieved bachelor’s degree from Pohang University of Science and Technology (POSTECH). I’ve worked with Hwanjo Yu when I was in POSTECH.

Publications

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2023

  1. EMNLP
    Conditional Natural Language Inference
    Youngwoo Kim, Razieh Rahimi, and James Allan,
    In Findings of the Association for Computational Linguistics: EMNLP 2023 2023
    PDF Code

2022

  1. SIGIR
    Alignment Rationale for Query-Document Relevance
    Youngwoo Kim, Razieh Rahimi, and James Allan,
    In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval 2022
    PDF

2021

  1. CIKM
    Query-driven Segment Selection for Ranking Long Documents
    Youngwoo Kim, Razieh Rahimi, Hamed Bonab, and James Allan,
    In Proceedings of the 30th ACM International Conference on Information and Knowledge Management 2021
    PDF

2020

  1. TOIS
    Explaining Text Matching on Neural Natural Language Inference
    Youngwoo Kim, Myungha Jang, and James Allan,
    ACM Transactions on Information Systems 2020
    PDF Code

2019

  1. ECIR Best paper
    Unsupervised Explainable Controversy Detection from Online News
    Youngwoo Kim, and James Allan,
    In European Conference on Information Retrieval 2019
    PDF Code
  2. FEVER
    FEVER Breaker’s Run of Team NbAuzDrLqg
    Youngwoo Kim, and James Allan,
    In Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER) 2019
    PDF

2014

  1. KBS
    Geotree: using spatial information for georeferenced video search
    Youngwoo Kim, Jinha Kim, and Hwanjo Yu,
    Knowledge-based systems 2014
    PDF

2012

  1. SIGKDD
    GeoSearch: georeferenced video retrieval system
    Youngwoo Kim, Jinha Kim, and Hwanjo Yu,
    In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining 2012
    PDF
  2. ISJ
    Edge detection based on morphological amoebas
    Won Yeol Lee, Young Woo Kim, Se Yun Kim, Jae Young Lim, and Dong Hoon Lim,
    The Imaging Science Journal 2012
    PDF

2009

  1. ICIP
    Edge detection using morphological amoebas in noisy images
    Won Yeol Lee, Se Yun Kim, Young Woo Kim, Jae Young Lim, and Dong Hoon Lim,
    In 2009 16th IEEE International Conference on Image Processing (ICIP) 2009
    PDF