publications

2026

1. CVPR

   Restore-R1: Efficient Image Restoration Agents via Reinforcement Learning with Multimodal LLM Perceptual Feedback

   Jianglin Lu, Yuanwei Wu, Ziyi Zhao, Hongcheng Wang, Felix Jimenez, Abrar Majeedi, and Yun Fu

   In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings track, 2026

   Bib

   @inproceedings{lu2026restorer1,
     title = {Restore-R1: Efficient Image Restoration Agents via Reinforcement Learning with Multimodal LLM Perceptual Feedback},
     author = {Lu, Jianglin and Wu, Yuanwei and Zhao, Ziyi and Wang, Hongcheng and Jimenez, Felix and Majeedi, Abrar and Fu, Yun},
     booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings track},
     year = {2026},
   }

2. CVPR

   Training-Free Cross-Modal Alignment via Anchor Profiles with Statistical Significance Testing

   Kuo Yang, Jianglin Lu, and Yun Fu

   In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings track, 2026

   Bib

   @inproceedings{yang2026trainingfree,
     title = {Training-Free Cross-Modal Alignment via Anchor Profiles with Statistical Significance Testing},
     author = {Yang, Kuo and Lu, Jianglin and Fu, Yun},
     booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings track},
     year = {2026},
   }

3. CVPR

   DUALVISION: RGB–Infrared Multimodal Large Language Models for Robust Visual Reasoning

   Abrar Majeedi, Zhiyuan Ruan, Ziyi Zhao, Hongcheng Wang, Jianglin Lu, and Yin Li

   In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings track, 2026

   Bib

   @inproceedings{majeedi2026dualvision,
     title = {DUALVISION: RGB--Infrared Multimodal Large Language Models for Robust Visual Reasoning},
     author = {Majeedi, Abrar and Ruan, Zhiyuan and Zhao, Ziyi and Wang, Hongcheng and Lu, Jianglin and Li, Yin},
     booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings track},
     year = {2026}
   }

4. ICLR

   Ref-Adv: Exploring MLLM Visual Reasoning in Referring Expression Tasks

   Qihua Dong, Yang Kuo, Ju Lin, Handong Zhao, Yitian Zhang, Yizhou Wang, Huimin Zeng, Jianglin Lu, and Yun Fu

   In The Fourteenth International Conference on Learning Representations (ICLR), 2026

   Bib PDF Code Website

   @inproceedings{dong2026refadv,
     title = {Ref-Adv: Exploring MLLM Visual Reasoning in Referring Expression Tasks},
     author = {Dong, Qihua and Kuo, Yang and Lin, Ju and Zhao, Handong and Zhang, Yitian and Wang, Yizhou and Zeng, Huimin and Lu, Jianglin and Fu, Yun},
     booktitle = {The Fourteenth International Conference on Learning Representations (ICLR)},
     year = {2026},
   }

5. ICLR

   Seeing Through Words: Controlling Visual Retrieval Quality with Language Models

   Jianglin Lu, Simon Jenni, Kushal Kafle, Jing Shi, Handong Zhao, and Yun Fu

   2026

   arXiv preprint, 2026

   Bib PDF Code HuggingFace

   @misc{lu2026seeingthroughwords,
     title = {Seeing Through Words: Controlling Visual Retrieval Quality with Language Models},
     author = {Lu, Jianglin and Jenni, Simon and Kafle, Kushal and Shi, Jing and Zhao, Handong and Fu, Yun},
     note = {arXiv preprint, 2026},
     year = {2026},
     huggingface = {https://huggingface.co/Johnny050407/QCQC},
   }

6. TFS

   Fuzzy Multi-Subspace Clustering

   Yangbo Wang, Jie Zhou, Mingli Song, Yue Guo, and Jianglin Lu

   IEEE Transactions on Fuzzy Systems, 2026

   Bib HTML

   @article{wang2026fuzzymultisubspace,
     title = {Fuzzy Multi-Subspace Clustering},
     author = {Wang, Yangbo and Zhou, Jie and Song, Mingli and Guo, Yue and Lu, Jianglin},
     journal = {IEEE Transactions on Fuzzy Systems},
     year = {2026}
   }

2025

1. NeurIPS

   The Indra Representation Hypothesis for Multimodal Alignment

   Jianglin Lu, Hailing Wang, Kuo Yang, Yitian Zhang, Simon Jenni, and Yun Fu

   In Advances in Neural Information Processing Systems, 2025

   Bib PDF Code

   @inproceedings{lu2025indra,
     title = {The Indra Representation Hypothesis for Multimodal Alignment},
     author = {Lu, Jianglin and Wang, Hailing and Yang, Kuo and Zhang, Yitian and Jenni, Simon and Fu, Yun},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2025},
   }

2. ICCV

   Outlier-Aware Post-Training Quantization for Image Super-Resolution

   Hailing Wang, Jianglin Lu, Yitian Zhang, and Yun Fu

   In International Conference on Computer Vision (ICCV), Highlight, 2025

   Bib PDF

   @inproceedings{wang2025outlieraware,
     title = {Outlier-Aware Post-Training Quantization for Image Super-Resolution},
     author = {Wang, Hailing and Lu, Jianglin and Zhang, Yitian and Fu, Yun},
     booktitle = {International Conference on Computer Vision ({ICCV}), <strong><span style="color: var(--global-theme-color);">Highlight</span></strong>},
     year = {2025},
   }

3. EMNLP

   Representation Potentials of Foundation Models for Multimodal Alignment: A Survey

   Jianglin Lu, Hailing Wang, Yi Xu, Yizhou Wang, Kuo Yang, and Yun Fu

   The 2025 Conference on Empirical Methods in Natural Language Processing, 2025

   Cited by Prof. Yoshua Bengio in the International AI Safety Report 2026

   Bib PDF Code

   @article{lu2025representationpotentialsurvey,
     title = {Representation Potentials of Foundation Models for Multimodal Alignment: A Survey},
     author = {Lu, Jianglin and Wang, Hailing and Xu, Yi and Wang, Yizhou and Yang, Kuo and Fu, Yun},
     journal = {The 2025 Conference on Empirical Methods in Natural Language Processing},
     note = {Cited by <a href="https://scholar.google.com/citations?user=kukA0LcAAAAJ&hl=en"><strong><span style="color: var(--global-theme-color);">Prof. Yoshua Bengio</span></strong></a> in the <a href="https://arxiv.org/pdf/2602.21012"><strong><span style="color: var(--global-theme-color);">International AI Safety Report 2026</span></strong></a>},
     year = {2025},
   }

4. EMNLP

   Unequal Scientific Recognition in the Age of LLMs

   Yixuan Liu, Abel Elekes, Jianglin Lu, Rodrigo Dorantes-Gilardi, and Albert-Laszlo Barabasi

   The 2025 Conference on Empirical Methods in Natural Language Processing, 2025

   Findings track of EMNLP

   Bib PDF

   @article{liu2025unequalscientificrecognition,
     title = {Unequal Scientific Recognition in the Age of LLMs},
     author = {Liu, Yixuan and Elekes, Abel and Lu, Jianglin and Dorantes-Gilardi, Rodrigo and Barabasi, Albert-Laszlo},
     journal = {The 2025 Conference on Empirical Methods in Natural Language Processing},
     note = {Findings track of EMNLP},
     year = {2025},
   }

5. ICLR

   Scale-Free Graph-Language Models

   Jianglin Lu, Yixuan Liu, Yitian Zhang, and Yun Fu

   In The Thirteenth International Conference on Learning Representations (ICLR), 2025

   Bib PDF Code

   @inproceedings{lu2025scalefreegraphlanguage,
     title = {Scale-Free Graph-Language Models},
     author = {Lu, Jianglin and Liu, Yixuan and Zhang, Yitian and Fu, Yun},
     booktitle = {The Thirteenth International Conference on Learning Representations (ICLR)},
     year = {2025},
   }

2024

1. PR

   Robust Self-expression Learning with Adaptive Noise Perception

   Yangbo Wang, Jie Zhou, Jianglin Lu, Jun Wan, Can Gao, and Qingshui Lin

   Pattern Recognition, 2024

   Bib HTML

   @article{wang2024robustselfexpression,
     title = {Robust Self-expression Learning with Adaptive Noise Perception},
     author = {Wang, Yangbo and Zhou, Jie and Lu, Jianglin and Wan, Jun and Gao, Can and Lin, Qingshui},
     journal = {Pattern Recognition},
     year = {2024}
   }

2. TCYB

   Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning

   Jianglin Lu, Jie Zhou, Yudong Chen, Witold Pedrycz, and Kwok-Wai Hung

   IEEE Transactions on Cybernetics, 2024

   Bib HTML

   @article{lu2024asymmetrictransferhashing,
     title = {Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning},
     author = {Lu, Jianglin and Zhou, Jie and Chen, Yudong and Pedrycz, Witold and Hung, Kwok-Wai},
     journal = {IEEE Transactions on Cybernetics},
     year = {2024}
   }

2023

1. NeurIPS

   Latent Graph Inference with Limited Supervision

   Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, and Yun Fu

   In Advances in Neural Information Processing Systems, 2023

   Bib PDF Code Website

   @inproceedings{lu2023latentgraphinference,
     title = {Latent Graph Inference with Limited Supervision},
     author = {Lu, Jianglin and Xu, Yi and Wang, Huan and Bai, Yue and Fu, Yun},
     booktitle = {Advances in Neural Information Processing Systems},
     year = {2023},
   }

2022

1. TOMM

   Deep Semantic and Attentive Network for Unsupervised Video Summarization

   Shenghua Zhong, Jingxu Lin, Jianglin Lu, Ahmed Fares, and Tongwei Ren

   ACM Transactions on Multimedia Computing, Communications, and Applications, 2022

   Bib HTML

   @article{zhong2022deepsemanticattentive,
     title = {Deep Semantic and Attentive Network for Unsupervised Video Summarization},
     author = {Zhong, Shenghua and Lin, Jingxu and Lu, Jianglin and Fares, Ahmed and Ren, Tongwei},
     journal = {ACM Transactions on Multimedia Computing, Communications, and Applications},
     year = {2022}
   }

2. IJMLC

   Global Structure-Guided Neighborhood Preserving Embedding for Dimensionality Reduction

   Can Gao, Yong Li, Jie Zhou, Witold Pedrycz, Zhihui Lai, Jun Wan, and Jianglin Lu

   International Journal of Machine Learning and Cybernetics, 2022

   Bib HTML

   @article{gao2022globalstructureguided,
     title = {Global Structure-Guided Neighborhood Preserving Embedding for Dimensionality Reduction},
     author = {Gao, Can and Li, Yong and Zhou, Jie and Pedrycz, Witold and Lai, Zhihui and Wan, Jun and Lu, Jianglin},
     journal = {International Journal of Machine Learning and Cybernetics},
     year = {2022}
   }

3. TNNLS

   Generalized Embedding Regression: A Framework for Supervised Feature Extraction

   Jianglin Lu, Zhihui Lai, Hailing Wang, Yudong Chen, Jie Zhou, and Linlin Shen

   IEEE Transactions on Neural Networks and Learning Systems, 2022

   Bib HTML

   @article{lu2022generalizedembeddingregression,
     title = {Generalized Embedding Regression: A Framework for Supervised Feature Extraction},
     author = {Lu, Jianglin and Lai, Zhihui and Wang, Hailing and Chen, Yudong and Zhou, Jie and Shen, Linlin},
     journal = {IEEE Transactions on Neural Networks and Learning Systems},
     year = {2022}
   }

4. INS

   Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization

   Jianglin Lu, Hailing Wang, Jie Zhou, Mengfan Yan, and Jiajun Wen

   Information Sciences, 2022

   Bib HTML

   @article{lu2022deepasymmetrichashing,
     title = {Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization},
     author = {Lu, Jianglin and Wang, Hailing and Zhou, Jie and Yan, Mengfan and Wen, Jiajun},
     journal = {Information Sciences},
     year = {2022}
   }

5. IJCAI

   Uncertainty-Guided Pixel Contrastive Learning for Semi-Supervised Medical Image Segmentation

   Tao Wang, Jianglin Lu, Zhihui Lai, Jiajun Wen, and Heng Kong

   In International Joint Conference on Artificial Intelligence, 2022

   Bib HTML

   @inproceedings{wang2022uncertaintyguidedpixelcontrastivelearning,
     title = {Uncertainty-Guided Pixel Contrastive Learning for Semi-Supervised Medical Image Segmentation},
     author = {Wang, Tao and Lu, Jianglin and Lai, Zhihui and Wen, Jiajun and Kong, Heng},
     booktitle = {International Joint Conference on Artificial Intelligence},
     year = {2022}
   }

2021

1. PR

   Low-Rank Adaptive Graph Embedding for Unsupervised Feature Extraction

   Jianglin Lu, Hailing Wang, Jie Zhou, Yudong Chen, Zhihui Lai, and Qinghua Hu

   Pattern Recognition, 2021

   Bib HTML

   @article{lu2021lowrankadaptivegraphembedding,
     title = {Low-Rank Adaptive Graph Embedding for Unsupervised Feature Extraction},
     author = {Lu, Jianglin and Wang, Hailing and Zhou, Jie and Chen, Yudong and Lai, Zhihui and Hu, Qinghua},
     journal = {Pattern Recognition},
     year = {2021}
   }

2. INS

   Target Redirected Regression with Dynamic Neighborhood Structure

   Jianglin Lu, Jingxu Lin, Zhihui Lai, Hailing Wang, and Jie Zhou

   Information Sciences, 2021

   Bib HTML

   @article{lu2021targetredirectedregression,
     title = {Target Redirected Regression with Dynamic Neighborhood Structure},
     author = {Lu, Jianglin and Lin, Jingxu and Lai, Zhihui and Wang, Hailing and Zhou, Jie},
     journal = {Information Sciences},
     year = {2021}
   }

3. ACM MM

   Local Graph Convolutional Networks for Cross-Modal Hashing

   Yudong Chen, Sen Wang, Jianglin Lu, Zhi Chen, Zheng Zhang, and Zi Huang

   In ACM International Conference on Multimedia, 2021

   Bib HTML

   @inproceedings{chen2021localgraphconvolutionalnetworks,
     title = {Local Graph Convolutional Networks for Cross-Modal Hashing},
     author = {Chen, Yudong and Wang, Sen and Lu, Jianglin and Chen, Zhi and Zhang, Zheng and Huang, Zi},
     booktitle = {ACM International Conference on Multimedia},
     year = {2021}
   }

4. ICME

   Progressive Distribution Alignment Based on Label Correction for Unsupervised Domain Adaptation

   Yong Li, Desheng Li, Yuwu Lu, Can Gao, Wenjing Wang, and Jianglin Lu

   In 2021 IEEE International Conference on Multimedia and Expo, 2021

   Bib HTML

   @inproceedings{li2021progressivedistributionalignment,
     title = {Progressive Distribution Alignment Based on Label Correction for Unsupervised Domain Adaptation},
     author = {Li, Yong and Li, Desheng and Lu, Yuwu and Gao, Can and Wang, Wenjing and Lu, Jianglin},
     booktitle = {2021 IEEE International Conference on Multimedia and Expo},
     year = {2021}
   }

2020

1. ICPR

   Label Self-Adaption Hashing for Image Retrieval

   Jianglin Lu, Zhihui Lai, Jingxu Lin, Qinghong Lin, and Jie Zhou

   In International Conference on Pattern Recognition, 2020

   Bib HTML

   @inproceedings{lu2020labelselfadaptionhashing,
     title = {Label Self-Adaption Hashing for Image Retrieval},
     author = {Lu, Jianglin and Lai, Zhihui and Lin, Jingxu and Lin, Qinghong and Zhou, Jie},
     booktitle = {International Conference on Pattern Recognition},
     year = {2020}
   }

2. ICPR

   Deep Superpixel Cut for Unsupervised Image Segmentation

   Qinghong Lin, Weichan Zhong, and Jianglin Lu

   In International Conference on Pattern Recognition, 2020

   Bib HTML

   @inproceedings{lin2020deepsuperpixelcut,
     title = {Deep Superpixel Cut for Unsupervised Image Segmentation},
     author = {Lin, Qinghong and Zhong, Weichan and Lu, Jianglin},
     booktitle = {International Conference on Pattern Recognition},
     year = {2020}
   }