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Hi there ๐Ÿ‘‹๐Ÿ‘‹

I'm Computer Engineer! โœจ Panic โœจ Always looking for sth interesting !

  • I'm currently research Natural Language Processing, Multi Modal Processing with vision
  • I'm interesting NLP, DeepLearning, Text style transfer, Translation, Paper Reveiw

Publications

  • Kyohoon Jin, Junho Lee, Juhwan Choi, Sangming Song and Youngbin Kim "Enhancing Effectiveness and Robustness in a Low-Resource Regime via Decision-Boundary-aware Data Augmentation", The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (COLING) [Link]
  • Juhwan Choi, Kyohoon Jin, Junho Lee, Sangming Song and Youngbin Kim "AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes", 2024 European Chapter of the Association for Computational Linguistics (EACL) Student Research Workshop [Link]
  • Juhwan Choi, Kyohoon Jin, Junho Lee, Sangmin Song and Youngbin Kim "SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels", 2023 International Conference on Learning Representations (ICLR) Tiny[Link]
  • KyoHoon Jin, JunHo Lee, JuHwan Choi, SooJin Jang and YoungBin Kim "Generative Data Augmentation via Wasserstein Autoencoder for Text Classification", 2022 International Conference on ICT Convergence (ICTC) [Link]

Domestic Publications

  • Kyohoon Jin, Junho Lee, Juhwan Choi, Sangmin Song, Soojin Jang and Youngbin Kim "ํ…์ŠคํŠธ ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•œ Wasserstein Autoencoder๋ฅผ ํ™œ์šฉํ•œ ์ƒ์„ฑ์  ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• (Generative Data Augmentation for Text Classification using Wasserstein Autoencoder)", KICS Winter Conference 2024"
  • Junho Lee, Sangmin Song, Juhwan Choi, Juhyoung Park, Kyohoon Jin, Youngbin Kim "๋‚ฏ์„  ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ ๊ณผ์ž‰์‹ ๋ขฐ ์™„ํ™” ํ…์ŠคํŠธ ์ฆ๊ฐ• ๊ธฐ๋ฒ• (Text Augmentation to Mitigate Overconfidence through Unfamiliar Data), Proceedings of HCI Korea 2023
  • JuHwan Choi, JunHo Lee, KyoHoon Jin, YeHoon Jang and YoungBin Kim "Variational Autoencoder๋ฅผ ํ™œ์šฉํ•œ ์˜๋ฏธ ๋ณด์กด ์ž์—ฐ์–ด ๋ฐ์ดํ„ฐ ์ฆ๊ฐ• ๊ธฐ๋ฒ• (Semantic Preservation Natural Language Data Augmentation via Variational Autoencoder), 2022 Summer Annual Conference of IEIE" [Link]
  • Yuchul Shin, Kyohoon Jin, Juhwan Choi, Junho Lee, Soojin Jang and Youngbin Kim "Semantic Preservation and Natural Language Data Augmentation via Variational Autoencoder", 2022 TechART [Link]
  • JunHo Lee, KyoHoon Jin and YoungBin Kim "๊ณ ์œ ๋ช…์‚ฌ๋ฅผ ํ™œ์šฉํ•œ Seed Lexicon ์„ ์ •๋ฐฉ์‹์˜ ํšจ์œจ์ ์ธ ๋‹ค๊ตญ์–ด ์ž„๋ฒ ๋”ฉ (Efficient Multilingual Embedding via Seed Lexicon Selection Method)", 2021 Korea Computer Congress (KCC) [Link]

Now Researching

(NLP)Language Model, Data Augment, Text Style Transfer

Languages and Tools

Pytorch, Tensorflow, TensorRT,

Panic's Projects

awesome-nlp icon awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

bert_hae icon bert_hae

BERT with History Answer Embedding for Conversational Question Answering

dev-conf-replay icon dev-conf-replay

๋น„๊ต์  ์ตœ๊ทผ์— ์ง„ํ–‰๋œ ๊ตญ๋‚ด IT ๋ฐ ๊ฐœ๋ฐœ์ž:computer: ์ปจํผ๋Ÿฐ์Šค ์˜์ƒ์˜ ๋‹ค์‹œ ๋ณด๊ธฐ:eyes: ๋งํฌ๋ฅผ ํ•œ๊ณณ์— ์ •๋ฆฌํ–ˆ์Šต๋‹ˆ๋‹ค!:four_leaf_clover:

gitignore icon gitignore

A collection of useful .gitignore templates

graph4nlp_demo icon graph4nlp_demo

This repo is to present various code demos on how to use our Graph4NLP library.

highway-env icon highway-env

A minimalist environment for decision-making in autonomous driving

kmario23 icon kmario23

short glimpse of my presence around the web :earth_americas:

long-summarization icon long-summarization

Resources for the NAACL 2018 paper "A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents"

nlp-progress icon nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

online_telegram_chatbot icon online_telegram_chatbot

ํ•œ๊ตญ์ธ๊ณต์ง€๋Šฅ์•„์นด๋ฐ๋ฏธ & SBA ์•„์นด๋ฐ๋ฏธ ์˜จ๋ผ์ธ ์ฑ—๋ด‡ ๊ต์œก์ž๋ฃŒ

parakqc icon parakqc

Parallel dataset of Korean Questions and Commands

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