Jeongwan Shin
About Me
Jeongwan is a researcher in the field of Natural Language Processing (NLP), with a focus on machine learning, natural language processing, abstractive summarization, fact correction and Large Language Model (LLM). He received his Ph.D. in computer science and engineering and is interested in forming an LLM-based ecosystem. Recently, as a postdoctoral researcher, he has been studying the integration of radar sensing with natural language and further aims to develop LLMs that enable autonomous systems to interact with the physical world through natural language.
Research Interests and Skills
- Natural Language Processing: Language Generation, In-context learning, Summarization, Text-Diffusion generation, Rainforment learning from human feedback
- Visual Language Processing: Video Question Ansering
- Machine Learning: Generative Model, Representation learning
- Radar & Autonomous Systems: mmWave Radar Processing, Radar-Language Alignment, Multimodal Reasoning for Autonomous Systems
- Programming: Pytorch, Pytorch lightning
- GPU server Build Management: Linux configuration and engineering, NAS, Docker
- Language Skills: Korean, English
News
- [Feb. 2026] Our paper, "Can Language Models Understand mmWave Data? Benchmarking Large Language Models for mmWave Radar-Based Human Understanding", has been accepted to CVPR Findings 2026.
- [Nov. 2025] Our paper, "ReFineVQA: Iterative Refinement of Video Description via Feedback Generation for Video Question Answering", has been accepted to WACV 2026.
- [Aug. 2025] Started a Postdoctoral Researcher position at DGIST (KAIST InnoCORE LLM Innovation Research Center), focusing on radar–language integration and autonomous systems.
- [May. 2025] Excited to share that our paper, "Cross-Modal Knowledge Distillation for Enhancing Domain-Specific Retrievers", has been accepted for presentation at the *Information Retrieval's Role in RAG Systems* (IR-RAG) at SIGIR 2025.
- [Mar. 2025] Our paper, "Does Video Language Models Really Understand the Video Contexts?", has been accepted to NAACL 2025 Student Research Workshop (SRW).
- [Sep. 2024] Our paper about Factuality Guided Diffusion-Based Abstractive Summarization is accepted to IEEE access 2024.
- [Jan. 2023] Our paper about Token-Level Fact Correction in Abstractive Summarization is accepted to IEEE access 2023.
Publications
International Conference
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CVPR findings 2026
The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2026, June 3-7, 2026PDF CVPR Findings -
WACV 2026
The IEEE/CVF Winter Conference on Applications of Computer Vision 2026, March 6-10, 2026PDF WACV -
EMNLP Industry 2025
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 2551–2563, November 4-9, 2025PDF EMNLP Industry -
NAACL
The 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025) will be held in Albuquerque, New Mexico from April 29–May 4, 2025.PDF NAACL SRW
International Journal
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Applied Computing eJournal
Applied Computing eJournal, 2024. -
IEEE access
Published in: IEEE access( Volume: 12), 2024. -
IEEE access
Published in: IEEE access( Volume: 11), 2023.
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Journal of KIISE
Korean Institute of Information Scientists and Engineers, vol.49, no.3, pp. 231-240, 2022.
Domestic journal
Domestic conference
Atomic Unit-based Post Editing for Hallucination Reduction Yonghwan Lee, Jeongwan Shin, Hyun-Je Song The 35th Annual Conference on Human Cognitive Language Technology, 2023. Multi-view Spectral Clustering for news articles Sang-Seok Park, Jeongwan Shin, Seyoung Park, Seong-Bae Park Korean Institute of Information Scientists and Engineers, Korea Computer Congress 2018 Generating Multi-Class Images Using a Generative Adversarial Network Jeongwan Shin, Yunseok Noh, Se-young Park Korean Institute of Information Scientists and Engineers, Korea Computer Congress 2017 Neural Conversational Model for Specific Domain Sujeong Choi, Jeongwan Shin, Ian Jung, Se-Young Park, Seong-Bae Park Korean Institute of Information Scientists and Engineers, Korea Software Congress 2017 Pattern Filtering for Knowledge Extraction Using Facts from Web Sol Kim, Jeongwan Shin, Se-Young Park, Sang-Jo Lee Korean Institute of Information Scientists and Engineers. 2015
Experience
Invited Talk
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Understanding the Objective Function of RLHF(From ChatGPT to Deepseek)PLACE: Kyungpook National University(2025)
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Token-Level Fact Correction in Abstractive SummarizationPLACE: Jeonbuk National University(2022)
Internship
KAIST Hangul Engineering Research Lab (Mar 2013 - Feb 2014) Development of Hangul-based Universal Phonetic System Developing keyboard applications for iPhone and Android Technology integration and call process development
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