Junchen Fu

Junchen Fu (付俊臣)

Pronunciation: Joon-chen Foo (/ˈdʒuːn tʃən fuː/)

University of Glasgow

PhD Candidate

School of Computing Science, IDA-section

Member of GAIR Lab

Email: j.fu.3@research.gla.ac.uk;

Google Scholar: Google Scholar Profile     Github: Google Scholar Profile     Twitter(X): Google Scholar Profile

About Me

I am a final-year PhD candidate at the University of Glasgow, advised by Prof. Joemon M. Jose, and have also been fortunate to be mentored by Dr. Alexandros Karatzoglou and Dr. Ioannis Arapakis. I was a visiting PhD student at Leiden University, advised by Prof. Zhaochun Ren and Prof. Suzan Verberne. Previously, I worked as a Research Assistant at Westlake University under the supervision of Prof. Fajie Yuan, focusing on modality-based recommender systems. I received my MSc in Computer Science from The Chinese University of Hong Kong, where I graduated with Dean’s List honors. I have authored over 10 papers as first, co-first, or corresponding author in premier AI conferences and journals.

My research focuses on Recommendation-Oriented Multimodal Foundation Models, with the central question of how to transform general-purpose multimodal foundation models into systems that can represent, generate, and personalize multimodal information for recommendation. Specifically, I study how representation and generation foundation models can be adapted into recommendation-oriented systems that better understand users, represent items, and support personalized information ecosystems.

Research Overview
Research framework for recommendation-oriented multimodal foundation models

My work mainly explores this direction from two perspectives:

  1. Recommendation-Oriented Representation

    I study how to adapt multimodal foundation models into recommendation-aligned representations in both continuous and discrete spaces. My work includes efficient continuous multimodal representation adaptation [ Adapter4Rec (WSDM'24), IISAN (SIGIR'24), IISAN-Versa (TKDE'25), CROSSAN (ArXiv'25) ], and discrete Semantic ID learning for generative recommendation [ DIGER (SIGIR'26) ].

  2. Recommendation-Oriented Generation

    I also explore how generative models can support recommender systems from the user and platform sides, including popular content generation on user side [ LLMPopcorn (ICASSP'26) ] and missing modality completion for item understanding on platform side [ MMPCBench (PR'26) ].

I enjoy tackling non-trivial research questions with simple yet effective solutions.
I am seeking to collaborate on a research project with self-motivated MSc students from UofG, particularly those interested in pursuing a PhD. the students who are interested in research towards premier AI conferences/journals are welcome to drop me an email.

Latest News

Oral Presentation/Invited Talk:

Workshop Summary:

Selected Publications

Note: Corresponding-author papers come from MSc/Undergraduate supervision at UofG or other universities.

2026

  1. Junchen Fu, Xuri Ge, Alexandros Karatzoglou, Ioannis Arapakis, Suzan Verberne, Joemon M. Jose, Zhaochun Ren.
    Differentiable Semantic ID for Generative Recommendation. [CODE]
    - Accepted by SIGIR 2026 (CORE Rank A*, CCF-A)
  2. Junchen Fu, Wenhao Deng, Kaiwen Zheng, Ioannis Arapakis, Yu Ye, Yongxin Ni, Joemon M. Jose, Xuri Ge.
    Benchmarking Multimodal Large Language Models for Missing Modality Completion in Product Catalogues.
    - Accepted by PR 2026 (CORE Rank A*, CCF-B, JCR Q1, IF=7.6)
  3. Junchen Fu, Xuri Ge, Kaiwen Zheng, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Yongxin Ni, Joemon M. Jose.
    LLMPopcorn: Exploring LLMs as Assistants for Popular Micro-video Generation. [CODE]
    - ICASSP 2026 (CCF-B)
  4. Yu Ye, Junchen Fu# (corresponding author), Yu Song, Kaiwen Zheng, Joemon M. Jose.
    Are Multimodal Embeddings Truly Beneficial for Recommendation? A Deep Dive into Whole vs. Individual Modalities. [CODE]
    - ECIR 2026 (CORE Rank A)

2025

  1. Junchen Fu, Xuri Ge, Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Kaiwen Zheng, Yongxin Ni, and Joemon M. Jose
    Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation. [CODE]
    - TKDE2025 (CORE Rank A*, CCF-A, JCR Q1, IF=10.4)
  2. Ziyi Zhuang, Hongji Li, Junchen Fu# (corresponding author), Jiacheng Liu, Joemon M. Jose, Youhua Li, Yongxin Ni.
    Frequency-Decoupled Distillation for Efficient Multimodal Recommendation.
    - CIKM2025 (CORE Rank A, CCF-B)
  3. Yaoqin He*, Junchen Fu*(co-first authors), Kaiwen Zheng, Songpei Xu, Fuhai Chen, Jie Li, Joemon M. Jose, and Xuri Ge.
    Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering.
    - ICML2025 (CORE Rank A*, CCF-A)

2024

  1. Xuri Ge*, Junchen Fu*(co-first authors), Fuhai Chen, Shan An, Nicu Sebe, Joemon Jose.
    Towards End-to-End Explainable Facial Action Unit Recognition via Vision-Language Joint Learning.
    - ACM MM'2024 (CORE Rank A*, CCF-A).
  2. Junchen Fu, Xuri Ge, Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Jie Wang, Joemon Jose.
    IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT. [CODE]
    - SIGIR'2024 (CORE Rank A*, CCF-A).
  3. Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan.
    Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights. [CODE]
    - WSDM'2024 (CORE Rank A, CCF-B).
Full Publication List

2026

  1. Nai-Xin Zhai, Weihua Cheng, Dexu Yu, Yikai Gu, Hanwen Du, Junchen Fu, Chenxi Huang, Yingwei Song, Liyuan Lillian Ma, Yang Ran, Youhua Li, Yongxin Ni.
    Aligning Human Sense: Calibrated Distributional Reward Learning for Video Generatio.
    - Accepted by ECCV 2026 (CORE Rank A*, CCF-B)
  2. Junchen Fu, Xuri Ge, Alexandros Karatzoglou, Ioannis Arapakis, Suzan Verberne, Joemon M. Jose, Zhaochun Ren.
    Differentiable Semantic ID for Generative Recommendation. [CODE]
    - Accepted by SIGIR 2026 (CORE Rank A*, CCF-A)
  3. Junchen Fu, Wenhao Deng, Kaiwen Zheng, Ioannis Arapakis, Yu Ye, Yongxin Ni, Joemon M. Jose, Xuri Ge.
    Benchmarking Multimodal Large Language Models for Missing Modality Completion in Product Catalogues.
    - Accepted by PR 2026 (CORE Rank A*, CCF-B, JCR Q1, IF=7.6)
  4. Junchen Fu, Xuri Ge, Kaiwen Zheng, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Yongxin Ni, Joemon M. Jose.
    LLMPopcorn: Exploring LLMs as Assistants for Popular Micro-video Generation. [CODE]
    - ICASSP 2026 (CCF-B)
  5. Kaiwen Zheng, Junchen Fu, Songpei Xu, Yaoqing He, Joemon M.Jose, Han Hu, Xuri Ge
    Focal-RegionFace: Generating Fine-Grained Multi-attribute Descriptions for Arbitrarily Selected Face Focal Regions.
    - Accepted by ICMR 2026 (CCF-B)
  6. Yu Ye, Junchen Fu# (corresponding author), Yu Song, Kaiwen Zheng, Joemon M. Jose.
    A Reproducibility Study of Multimodal Embeddings for Recommender Systems. [CODE]
    - Accepted by IJMIR 2026 (JCR Q2, IF=2.9), Extension of ECIR2026
  7. Yu Ye, Junchen Fu# (corresponding author), Yu Song, Kaiwen Zheng, Joemon M. Jose.
    Are Multimodal Embeddings Truly Beneficial for Recommendation? A Deep Dive into Whole vs. Individual Modalities. [CODE]
    - ECIR 2026 (CORE Rank A)
  8. Junchen Fu*, Aravindhan Ashok* (co-first authors), Chengli Zhai, Kaiwen Zheng, Yu Song, Ziyi Zhang, Zhiwei Zheng, Yongxin Ni, Joemon M. Jose.
    Do LLMs Have Stable Personalities? A Comprehensive Investigation into Big Five Profiling. [CODE]
    - Accepted by ICANN 2026 (CCF-C)
  9. Hui Ye, Xuri Ge, Junqi Wang, Junchen Fu, Xin Xin, Jiao Xue, Yao Chen, Pengjie Ren, Zhumin Chen.
    Beyond efficient fine-tuning: Efficient hybrid fine-tuning of CLIP models guided by explainable ViT attention. [CODE]
    - Accepted by IPM 2026 (CORE Rank A, CCF-B, JCR Q1, IF=6.9)

2025

  1. Junchen Fu, Xuri Ge, Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Kaiwen Zheng, Yongxin Ni, and Joemon M. Jose
    Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation. [CODE]
    - TKDE2025 (CORE Rank A*, CCF-A, JCR Q1, IF=10.4)
  2. Zichen Yuan, Lifan Sun, Yucen Zhuang, Yue Wang, Xinyuan Song, Tianqi Xu, Siyuan Li, Junchen Fu, Youhua Li, Sirui Hong, Jiaqi Chen, Joemon M. Jose, Yongxin Ni.
    SOLAR: Serendipity Optimized Language Model Aligned for Recommendation [CODE].
    - EMNLP 2025 (Finding)
  3. Yongxin Ni, Yu Cheng, Xiangyan Liu, Junchen Fu, Youhua Li, Xiangnan He, Yongfeng Zhang, Fajie Yuan.
    A Content-Driven Micro-Video Recommendation Dataset at Scale. [CODE]
    - CIKM2025 (CORE Rank A, CCF-B)
  4. Ziyi Zhuang, Hongji Li, Junchen Fu# (corresponding author), Jiacheng Liu, Joemon M. Jose, Youhua Li, Yongxin Ni.
    Frequency-Decoupled Distillation for Efficient Multimodal Recommendation.
    - CIKM2025 (CORE Rank A, CCF-B)
  5. Yaoqin He*, Junchen Fu*(co-first authors), Kaiwen Zheng, Songpei Xu, Fuhai Chen, Jie Li, Joemon M. Jose, and Xuri Ge.
    Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering.
    - ICML2025 (CORE Rank A*, CCF-A)
  6. Junchen Fu, Yongxin Ni, Joemon M. Jose, Ioannis Arapakis, Kaiwen Zheng, Youhua Li, and Xuri Ge.
    CROSSAN: Towards Efficient and Effective Adaptation of Multiple Multimodal Foundation Models for Sequential Recommendation.
    -Arxiv 2025 (Preprint)
  7. Youhua Li, Ersheng Ni, Yihao Liu, Sibo Xu, Tianyi Xu, Mingxuan Wu, Junchen Fu, Yucheng Zhang, Yuanqi He, Xinyuan Song, Yongxin Ni.
    Bridging NIP and MLM: A Unified Meta-Learning Framework for Sequential Recommendation.
    - TKDD2025 (CCF-B, JCR Q1, IF=4.8)
  8. Kaiwen Zheng, Xuri Ge, Junchen Fu, Jun Peng, Joemon M. Jose.
    Multimodal Representation Learning Techniques for Comprehensive Facial State Analysis.
    - ICME2025 (CORE Rank A, CCF-B)
  9. Hui Han, Siyuan Li, Jiaqi Chen, Yiwen Yuan, Yuling Wu, Yufan Deng, Chak Tou Leong, Hanwen Du, Junchen Fu, Youhua Li, Jie Zhang, Chi Zhang, Li-jia Li, Yongxin Ni.
    Human-Aligned Video Generation Benchmark.
    - CVPR'2025 (CORE Rank A*, CCF-A)
  10. Ziyi Zhuang, Hanwen Du, Hui Han, Youhua Li, Junchen Fu, Joemon M. Jose, Yongxin Ni.
    Bridging the Gap: Teacher-Assisted Wasserstein Knowledge Distillation for Efficient Multi-Modal Recommendation.
    - ACM WWW'2025 (CORE Rank A*, CCF-A)
  11. Zhiyu Liu, Junchen Fu# (corresponding author), Kaiwen Zheng, Joemon M. Jose.
    Exploring Multimodal Pre-trained Models for Speech Emotion Recognition.
    - ACM WWW'2025 Workshop
  12. Hongji Li, Hanwen Du, Youhua li, Junchen Fu, Chunxiao Li, Ziyi Zhuang, Jiakang Li, Yongxin Ni.
    Teach Me How to Denoise: a Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration [CODE].
    - ACM WSDM'2025 (CORE Rank A, CCF-B, Best of WSDM)

2024

  1. Xuri Ge*, Junchen Fu*(co-first authors), Fuhai Chen, Shan An, Nicu Sebe, Joemon Jose.
    Towards End-to-End Explainable Facial Action Unit Recognition via Vision-Language Joint Learning.
    - ACM MM'2024 (CORE Rank A*, CCF-A).
  2. Junchen Fu, Xuri Ge, Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Jie Wang, Joemon Jose.
    IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT. [CODE]
    - SIGIR'2024 (CORE Rank A*, CCF-A).
  3. Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan.
    Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights. [CODE]
    - WSDM'2024 (CORE Rank A, CCF-B).
  4. Jiaqi Zhang, Yu Cheng, Yongxin Ni, Yunzhu Pan, Zheng Yuan, Junchen Fu, Youhua Li, Jie Wang, Fajie Yuan.
    NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation. [CODE]
    - TPAMI2024 (CORE Rank A*, CCF-A, JCR Q1, IF=20.8)

2023

  1. Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni.
    Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited. [CODE]
    - SIGIR'2023 (CORE Rank A*, CCF-A)

2022

  1. Junchen Fu and Zhaohui Qi.
    A TDF-WNSP-WLFM algorithm for product recommendation based on multiple types of implicit user behavior.
    - The Journal of Supercomputing 2022 (CORE Rank B, CCF-C, JCR Q2, IF=2.5)

Datasets

Work Experience

Education Background

MSc Supervision

Graduate Teaching Assistant

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Honors and Awards