I’m a Ph.D. candidate in the Data Intelligence and Learning Lab (DIAL Lab) at Sungkyunkwan University (SKKU), where I’m fortunate to be advised by Prof. Jongwuk Lee. I received my B.S. degree in Mechanical Engineering from SKKU in 2020. My research spans diverse recommendation tasks, including Traditional Collaborative Filtering, Sequential/Session-based Recommendation, Conversational Recommendation, and Generative Recommendation. Recently, I’ve been exploring the integration of large language models and multimodal data with recommendation systems. My Curriculum Vitae is Here.

Publications

Improving Linear Item-Item Recommender Models for Data Bias, Semantics, and Temporality [slide]
Seongmin Park (Committee: Jee-Hyong Lee, Hogun Park, Jae-Pil Heo, Joonseok Lee, Jongwuk Lee)
Ph.D. Dissertation

International Conferences

MergeRec: Model Merging for Data-Isolated Cross-Domain Sequential Recommendation [paper] [code]
Hyunsoo Kim*, Jaewan Moon*, Seongmin Park, Jongwuk Lee (* : equal contribution)
KDD 2026, Jeju, Republic of Korea (Acceptance Rate: 20%)

Enhancing Time Awareness in Generative Recommendation [paper] [code] [slide]
Sunkyung Lee, Seongmin Park, Jonghyo Kim, Mincheol Yoon, Jongwuk Lee
EMNLP 2025 Findings, Suzhou, China

MUFFIN: Mixture of User-Adaptive Frequency Filtering for Sequential Recommendation [paper] [code] [slide]
Ilwoong Baek*, Mincheol Yoon*, Seongmin Park, Jongwuk Lee (* : equal contribution)
CIKM 2025, Seoul, Republic of Korea (Acceptance Rate: 27%, 443/1627)

LLM-Enhanced Linear Autoencoders for Recommendation [paper] [code] [poster]
Jaewan Moon*, Seongmin Park*, Jongwuk Lee (* : equal contribution)
CIKM 2025, Seoul, Republic of Korea (Acceptance Rate: 30.6%, 185/604; short paper track)

Why is Normalization Necessary for Linear Recommenders? [paper] [code] [slide] [poster]
Seongmin Park, Mincheol Yoon, Hye-young Kim, Jongwuk Lee
SIGIR 2025, Padua, Italy (Acceptance Rate: 21.5%, 238/1105)

Linear Item-Item Models with Neural Knowledge for Session-based Recommendation [paper] [code] [slide]
Minjin Choi, Sunkyung Lee, Seongmin Park, Jongwuk Lee
SIGIR 2025, Padua, Italy (Acceptance Rate: 21.5%, 238/1105)

Empowering Retrieval-based Conversational Recommendation with Contrasting User Preferences [paper] [code] [slide]
Heejin Kook*, Junyoung Kim*, Seongmin Park, Jongwuk Lee (* : equal contribution)
NAACL 2025, Albuquerque, New Mexico, USA (Acceptance Rate: 22.15%, 719/3246)

Temporal Linear Item-Item Model for Sequential Recommendation [paper] [code] [slide]
Seongmin Park*, Mincheol Yoon*, Minjin Choi, Jongwuk Lee (* : equal contribution)
WSDM 2025, Hannover, Germany (Acceptance Rate: 17.3%, 106/614; Oral Presentation (Top 6.5%))

Toward a Better Understanding of Loss Functions for Collaborative Filtering [paper] [code] [slide]
Seongmin Park, Mincheol Yoon, Jae-woong Lee, Hogun Park, Jongwuk Lee
CIKM 2023, Birmingham, UK (Acceptance Rate: 24%, 354/1472)

uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering [paper] [code] [poster]
Jae-woong Lee, Seongmin Park, Mincheol Yoon, Jongwuk Lee
SIGIR 2023, Taipei, Taiwan (Acceptance Rate: 25.12%, 154/613; short paper track)

Bilateral Self-unbiased Learning from Biased Implicit Feedback [paper] [code] [slide] [poster]
Jae-woong Lee, Seongmin Park, Joonseok Lee, Jongwuk Lee
SIGIR 2022, Madrid, Spain (Acceptance Rate: 20%, 161/794)

Dual Unbiased Recommender Learning for Implicit Feedback [paper] [code]
Jae-woong Lee, Seongmin Park, Jongwuk Lee
SIGIR 2021, Virtual Event (Acceptance Rate: 27.6%, 145/526; short paper track)

Domestic Conferences and Journals

LLM-based Conversational Recommender Systems Using User/Item Preference Reasoning Paths [paper]
Hyeri Lee, Heejin Kook, Seongmin Park, Jongwuk Lee
Journal of KIISE (JOK) Vol.52 No.10 [2025]: 890-899, Oct 2025

Enhancing LLM-based Zero-Shot Conversational Recommendation via Reasoning Path [paper]
Heejin Kook, Seongmin Park, Jongwuk Lee
Journal of KIISE (JOK) Vol.52 No.7 [2025]: 617-626, Jul 2025

Evaluation and Analysis of Knowledge on the Movie Domain of Large Language Models through Chain of Thought Prompting [paper]
Jeongwoo Na*, Heejin Kook*, Seongmin Park, Jaewan Moon, Jongwuk Lee (* : equal contribution)
Korea Computer Congress, Jun 2023

Professional Services

Conference Reviewer

• 2026: The ACM Web Conference (WWW)
• 2026: ACM International Conference on Web Search and Data Mining (WSDM)
• 2024-2026: International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

Journal Reviewer

• 2025: IEEE Transactions on Consumer Electronics (JCR 2024 IF: 10.9, Q1)
• 2025: ACM Transactions on Intelligent Systems and Technology (JCR 2024 IF: 6.6, Q1)

External Reviewer

• NeurIPS (2022, 2023, 2025), WWW (2024), SIGIR (2023), WSDM (2022), AAAI (2022), KDD (2022), EMNLP (2022), EACL (2021)

Honors and Awards

• 2023: 2nd Place (Minister Award), 6th Stage II AI Grand Challenge: Policy Support AI [link]
• 2023: Excellence Prize, SKKU Graduate Student Paper Awards (8/140 teams; KRW 4,000,000) [link]
• 2023: 4th Place (Minister Award), 6th Stage I AI Grand Challenge: Policy Support AI [link]
• 2022: 1st Place (Minister Award), 5th Stage III AI Grand Challenge: Math Word Problem Solving [link]
• 2021: Participation Prize, SKKU Graduate Student Paper Awards (25/200 people; KRW 4,000,000) [link]
• 2021: 3rd Place (Minister Award), 5th Stage II AI Grand Challenge: Math Word Problem Solving
• 2015: Silver Prize, Undergraduate Korean Fluid Engineering Competition