Please check my Curriculum Vitae for more information!

• Graduate student @ Department of Artificial Intelligence, Chung-Ang University
• E-mail: [email protected] / [email protected]
• Personal Blog: c-juhwan.github.io
• LinkedIn: linkedin.com/in/cjuhwan99
• Research Interest: Natural Language Processing, Deep Learning

• Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation

  • Juhwan Choi, Jungmin Yun, Kyohoon Jin and YoungBin Kim
  • arXiv Preprint arxiv:2404.09682
  • Paper

• Don't be a Fool: Pooling Strategies in Offensive Language Detection from User-Intended Adversarial Attacks

  • Seunguk Yu, Juhwan Choi and YoungBin Kim
  • NAACL 2024 Findings
  • Paper

• Enhancing Effectiveness and Robustness in a Low-Resource Regime via Decision-Boundary-aware Data Augmentation

  • Kyohoon Jin, Junho Lee, Juhwan Choi, Sangmin Song and YoungBin Kim
  • LREC-COLING 2024
  • Paper

• Colorful Cutout: Enhancing Image Data Augmentation with Curriculum Learning

  • Juhwan Choi and YoungBin Kim
  • ICLR 2024 Tiny Papers
  • Paper | Code

• Adverb Is the Key: Simple Text Data Augmentation with Adverb Deletion

  • Juhwan Choi and YoungBin Kim
  • ICLR 2024 Tiny Papers
  • Paper | Code

• AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes

  • Juhwan Choi, Kyohoon Jin, Junho Lee, Sangmin Song and YoungBin Kim
  • EACL 2024 Student Research Workshop
  • Paper | Code | Poster

• GPTs Are Multilingual Annotators for Sequence Generation Tasks

  • Juhwan Choi, Eunju Lee, Kyohoon Jin, and YoungBin Kim
  • EACL 2024 Findings
  • Paper | Poster

• SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels

  • Juhwan Choi, Kyohoon Jin, Junho Lee, Sangmin Song and YoungBin Kim
  • ICLR 2023 Tiny Papers
  • Paper | Review | Code
  • Selected as notable work with presentation

• Generative Data Augmentation via Wasserstein Autoencoder for Text Classification

  • Kyohoon Jin, Junho Lee, Juhwan Choi, Soojin Jang and YoungBin Kim
  • The 13th International Conference on ICT Convergence
  • Paper | Code

• 텍스트 분류를 위한 Wasserstein Autoencoder를 활용한 생성적 데이터 증강
  • Kyohoon Jin, Junho Lee, Juhwan Choi, Sangmin Song, Soojin Jang and YoungBin Kim
  • 2024년도 한국통신학회 동계종합학술발표회
• 소프트 라벨을 적용한 규칙 기반 텍스트 데이터 증강 기법
  • Juhwan Choi, Junho Lee, Sangmin Song, Kyohoon Jin and YoungBin Kim
  • 대한전자공학회 2023년도 하계종합학술대회
  • Paper | Poster
• 감정 간의 관계를 고려한 지도 대조 학습 기반 감정 인식
  • Dongje Yoo, Kyunghoon Jeon, Juhwan Choi and YoungBin Kim
  • 대한전자공학회 2023년도 하계종합학술대회
  • Paper
• KITE: 한국어 고의 오탈자를 활용한 텍스트 데이터 증강 방법론
  • Seunguk Yu, Juhwan Choi, Heejae Suh, Kyohoon Jin and YoungBin Kim
  • 한국HCI학회 2023년도 학술대회
  • Paper
• 낯선 데이터를 활용한 과잉신뢰 완화 텍스트 증강 기법
  • Junho Lee, Sahngmin Song, Juhwan Choi, Juhyoung Park, Kyohoon Jin and YoungBin Kim
  • 한국HCI학회 2023년도 학술대회
  • Paper | Presentation
• Semantic Preservation and Natural Language Data Augmentation via Variational Autoencoder
  • Yuchul Shin, Kyohoon Jin, Juhwan Choi, Junho Lee, Soojin Jang and YoungBin Kim
  • TechArt
  • Paper
• Variational Autoencoder 기반 의미 보존 자연어 데이터 증강 기법
  • Juhwan Choi, Junho Lee, Kyohoon Jin, Yehoon Jang, Soojin Jang and YoungBin Kim
  • 대한전자공학회 2022년도 하계종합학술대회
  • Paper | Presentation

• Native: Korean
• Fluent: English

• Familiar: Python | C | C++
• Experienced: MATLAB

• Familiar: Pytorch | HuggingFace | Numpy | Pandas

• Familiar: Git