Please check my Curriculum Vitae for more information!
- Graduate student @ Department of Artificial Intelligence, Chung-Ang University
- E-mail: gold32317@gmail.com / gold5230@cau.ac.kr
- Personal Blog: c-juhwan.github.io
- LinkedIn: linkedin.com/in/cjuhwan99
- Research Interest: Natural Language Processing, Deep Learning
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Questioning Internal Knowledge Structure of Large Language Models Through the Lens of the Olympic Games
- Juhwan Choi and YoungBin Kim
- arXiv Preprint arXiv:2409.06518
- Paper
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VolDoGer: LLM-assisted Datasets for Domain Generalization in Vision-Language Tasks
- Juhwan Choi, Junehyoung Kwon, Jungmin Yun, Seunguk Yu and YoungBin Kim
- arXiv Preprint arXiv:2407.19795
- Paper
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UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation
- Juhwan Choi, Yeonghwa Kim, Seunguk Yu, Jungmin Yun and YoungBin Kim
- EMNLP 2024
- Paper
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Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation
- Juhwan Choi, Jungmin Yun, Kyohoon Jin and YoungBin Kim
- EMNLP 2024
- Paper
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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
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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
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Colorful Cutout: Enhancing Image Data Augmentation with Curriculum Learning
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Adverb Is the Key: Simple Text Data Augmentation with Adverb Deletion
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AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes
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GPTs Are Multilingual Annotators for Sequence Generation Tasks
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SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels
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Generative Data Augmentation via Wasserstein Autoencoder for Text Classification
- ๊ธฐ๊ณ๋ฒ์ญ์์ ํจ์จ์ ์ธ ๋๋ฉ์ธ ์ ์์ ์ํ ์ ์ํ ๋ฐ์ดํฐ์คํ ์ด ๋ฆฌ์ฌ์ด์ง
- Jinhee Jang, Juhwan Choi, Jungmin Yun and YoungBin Kim
- ๋ํ์ ์๊ณตํํ 2024๋ ๋ ํ๊ณ์ข ํฉํ์ ๋ํ
- Paper
- ๊ฐ์ ๊ฐ์ ๊ด๊ณ๋ฅผ ๊ณ ๋ คํ ์ง๋ ๋์กฐ ํ์ต ๊ธฐ๋ฐ ๊ฐ์ ์ธ์
- Dongje Yoo, Kyunghoon Jeon, Juhwan Choi and YoungBin Kim
- ๋ํ์ ์๊ณตํํ 2023๋ ๋ ํ๊ณ์ข ํฉํ์ ๋ํ
- Paper
- KITE: ํ๊ตญ์ด ๊ณ ์ ์คํ์๋ฅผ ํ์ฉํ ํ
์คํธ ๋ฐ์ดํฐ ์ฆ๊ฐ ๋ฐฉ๋ฒ๋ก
- Seunguk Yu, Juhwan Choi, Heejae Suh, Kyohoon Jin and YoungBin Kim
- ํ๊ตญHCIํํ 2023๋ ๋ ํ์ ๋ํ
- Paper
- ๋ฏ์ ๋ฐ์ดํฐ๋ฅผ ํ์ฉํ ๊ณผ์์ ๋ขฐ ์ํ ํ
์คํธ ์ฆ๊ฐ ๊ธฐ๋ฒ
- Junho Lee, Sahngmin Song, Juhwan Choi, Juhyoung Park, Kyohoon Jin and YoungBin Kim
- ํ๊ตญHCIํํ 2023๋ ๋ ํ์ ๋ํ
- Paper | Presentation
- Variational Autoencoder ๊ธฐ๋ฐ ์๋ฏธ ๋ณด์กด ์์ฐ์ด ๋ฐ์ดํฐ ์ฆ๊ฐ ๊ธฐ๋ฒ
- Juhwan Choi, Junho Lee, Kyohoon Jin, Yehoon Jang, Soojin Jang and YoungBin Kim
- ๋ํ์ ์๊ณตํํ 2022๋ ๋ ํ๊ณ์ข ํฉํ์ ๋ํ
- Paper | Presentation
- Native: Korean
- Fluent: English
- Familiar: Python
- Experienced: MATLAB | C | C++
- Familiar: Pytorch | HuggingFace Transformers | NumPy | Pandas
- Familiar: Git | CLI