@inproceedings{macridvae:2019,
 author = {Ma, Jianxin and Zhou, Chang and Cui, Peng and Yang, Hongxia and Zhu, Wenwu},
 title = {Learning Disentangled Representations for Recommendation},
 booktitle = {Advances in Neural Information Processing Systems},
 volume = {32},
 pages        = {5712--5723},
 year = {2019}
}

@inproceedings{RecVAE:2020,
    author = {Shenbin, Ilya and Alekseev, Anton and Tutubalina, Elena and Malykh, Valentin and Nikolenko, Sergey I.},
    title = {RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback},
    year = {2020},
    booktitle = {WSDM},
    pages = {528–536}
}

@inproceedings{ADDVAE:2022,
    author = {Tran, Nhu-Thuat and Lauw, Hady W.},
    title = {Aligning Dual Disentangled User Representations from Ratings and Textual Content},
    year = {2022},
    booktitle = {KDD},
    pages = {1798–1806}
}

@inproceedings{TopicVAE:2022,
    author = {Guo, Zhiqiang and Li, Guohui and Li, Jianjun and Chen, Huaicong},
    title = {TopicVAE: Topic-Aware Disentanglement Representation Learning for Enhanced Recommendation},
    year = {2022},
    booktitle = {Proceedings of the 30th ACM MM},
    pages = {511–520}
}

@inproceedings{MDCVAE:2022,
    author = {Zhu, Yaochen and Chen, Zhenzhong},
    title = {Mutually-Regularized Dual Collaborative Variational Auto-Encoder for Recommendation Systems},
    year = {2022},
    booktitle = {TheWebConf. },
    pages = {2379–2387}
}

@inproceedings{MultiVAE:2018,
    author = {Liang, Dawen and Krishnan, Rahul G. and Hoffman, Matthew D. and Jebara, Tony},
    title = {Variational Autoencoders for Collaborative Filtering},
    year = {2018},
    booktitle = {Proceedings of the 2018 World Wide Web Conference},
    pages = {689–698}
}

@inproceedings{betavae:2017,
    title={beta-{VAE}: Learning Basic Visual Concepts with a Constrained Variational Framework},
    author={Irina Higgins and Loic Matthey and Arka Pal and Christopher Burgess and Xavier Glorot and Matthew Botvinick and Shakir Mohamed and Alexander Lerchner},
    booktitle={ICLR},
    year={2017}
}

@article{betavae:2018,
  author       = {Christopher P. Burgess and
                  Irina Higgins and
                  Arka Pal and
                  Lo{\"{\i}}c Matthey and
                  Nick Watters and
                  Guillaume Desjardins and
                  Alexander Lerchner},
  title        = {Understanding disentangling in {\(\beta\)}-VAE},
  journal      = {CoRR},
  year         = {2018},
  url          = {http://arxiv.org/abs/1804.03599}
}
  \\volume       = {abs/1804.03599}, }

@article{SemMacridVAE:2023,
  author={Wang, Xin and Chen, Hong and Zhou, Yuwei and Ma, Jianxin and Zhu, Wenwu},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.}, 
  title={Disentangled Representation Learning for Recommendation}, 
  year={2023},
  volume={45},
  number={1},
  pages={408--424}
  }


@article{computational_OT:2019,
  author       = {Gabriel Peyr{\'{e}} and
                  Marco Cuturi},
  title        = {Computational Optimal Transport},
  journal      = {Found. Trends Mach. Learn.},
  volume       = {11},
  number       = {5-6},
  pages        = {355--607},
  year         = {2019}
}


@inproceedings{highway_network:2015,
     author = {Srivastava, Rupesh K and Greff, Klaus and Schmidhuber, J\"{u}rgen},
     booktitle = {Advances in Neural Information Processing Systems},
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     year = {2015}
}


@article{RLReview:2013,
    author = {Bengio, Yoshua and Courville, Aaron and Vincent, Pascal},
    title = {Representation Learning: A Review and New Perspectives},
    year = {2013},
    volume = {35},
    journal = {IEEE Trans. Pattern Anal. Mach. Intell.},
    pages = {1798–1828}
}


@inproceedings{disen_factorize:2018,
  author       = {Hyunjik Kim and
                  Andriy Mnih},
  title        = {Disentangling by Factorising},
  booktitle    = {ICML},
  pages        = {2654--2663},
  year         = {2018}
}


@article{isolating_vae:2018,
  author       = {Tian Qi Chen and
                  Xuechen Li and
                  Roger B. Grosse and
                  David Duvenaud},
  title        = {Isolating Sources of Disentanglement in Variational Autoencoders},
  journal      = {CoRR},
  year         = {2018},
  url          = {http://arxiv.org/abs/1802.04942}
}
 %  volume       = {abs/1802.04942}, year         = {2018}, url          = {http://arxiv.org/abs/1802.04942}}


@InProceedings{ChallengeDisenRL:2019,
  title = 	 {Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations},
  author =       {Locatello, Francesco and Bauer, Stefan and Lucic, Mario and Raetsch, Gunnar and Gelly, Sylvain and Sch{\"o}lkopf, Bernhard and Bachem, Olivier},
  booktitle = 	 {ICML},
  pages = 	 {4114--4124},
  year = 	 {2019}
}


@inproceedings{curcodis:2023,
  author    = {Xin Wang and Zirui Pan and Yuwei Zhou and Hong Chen and Chendi Ge and Wenwu Zhu},
  title     = {Curriculum Co-disentangled Representation Learning across Multiple
Environments for Social Recommendation},
  booktitle = {ICML},
pages        = {36174--36192},
  year      = {2023},
}


@inproceedings{Sinkformer:2022,
  author       = {Michael E. Sander and
                  Pierre Ablin and
                  Mathieu Blondel and
                  Gabriel Peyr{\'{e}}},
  title        = {Sinkformers: Transformers with Doubly Stochastic Attention},
  booktitle    = {AISTATS},
  pages        = {3515--3530},
  year         = {2022}
}



@InProceedings{AutoDiff:2018,
  title = 	 {Learning Generative Models with Sinkhorn Divergences},
  author = 	 {Genevay, Aude and Peyre, Gabriel and Cuturi, Marco},
  booktitle = 	 {AISTATS},
  pages = 	 {1608--1617},
  year = 	 {2018}
}


@inproceedings{sinkhorn_distance:2013,
 author = {Cuturi, Marco},
 booktitle = {NeurIPS},
 title = {Sinkhorn Distances: Lightspeed Computation of Optimal Transport},
 volume = {26},
 year = {2013}
}


@inproceedings{ECRTM:2023,
    title={Effective neural topic modeling with embedding clustering regularization},
    author={Wu, Xiaobao and Dong, Xinshuai and Nguyen, Thong and Luu, Anh Tuan},
    booktitle={International Conference on Machine Learning},
    pages        = {37335--37357},
    year={2023},
}


@inproceedings{MESH:2023,
    title     = {Unlocking Slot Attention by Changing Optimal Transport Costs},
    author    = {Zhang, Yan and Zhang, David W and Lacoste-Julien, Simon and Burghouts, Gertjan J and Snoek, Cees GM},
    booktitle = {ICML},
    volume       = {202},
    pages        = {41931--41951},
    year      = {2023}
}


@inproceedings{Align_transformer:2021,
  author       = {Shujian Zhang and
                  Xinjie Fan and
                  Huangjie Zheng and
                  Korawat Tanwisuth and
                  Mingyuan Zhou},
  title        = {Alignment Attention by Matching Key and Query Distributions},
  booktitle    = {Advances in Neural Information Processing Systems},
  pages        = {13444--13457},
  year         = {2021}
}


@inproceedings{OTKGE:2022,
    title={{OTKGE}: Multi-modal Knowledge Graph Embeddings via Optimal Transport},
    author={Zongsheng Cao and Qianqian Xu and Zhiyong Yang and Yuan He and Xiaochun Cao and Qingming Huang},
    booktitle={NeurIPS},
    pages = {39090--39102},
    year={2022}
}


@inproceedings{ctr:2011,
  author = {Chong Wang and David M. Blei},
  title =        {Collaborative topic modeling for recommending scientific articles},
  booktitle =    {KDD},
  year =         {2011},
  pages =        {448--456}
}


@inproceedings{cdl:2015,
  author = {Hao Wang and Naiyan Wang and Dit-Yan Yeung},
  title =        { Collaborative Deep Learning for Recommender Systems},
  booktitle =    {KDD},
  year =         {2015},
  pages =        {1235--1244}
}


@inproceedings{cvae:2017,
  author = {Xiaopeng Li and James She},
  title =        {Collaborative Variational Autoencoder for Recommender Systems},
  booktitle =    {KDD},
  year =         {2017},
  pages =        {305--314}
}


@inproceedings{convmf:2016,
  author = {Dong Hyun Kim and Chanyoung Park and Jinoh Oh and Sungyoung Lee and Hwanjo Yu},
  title =        {Convolutional Matrix Factorization for Document Context-Aware Recommendation},
  booktitle =    {RecSys},
  year =         {2016},
  pages =        {233--240}
}


@inproceedings{gate:2019,
  author = {Chen Ma and Peng Kang and Bin Wu and Qinglong Wang and Xue Liu},
  title =        {Gated Attentive-Autoencoder for Content-Aware Recommendation},
  booktitle =    {WSDM},
  year =         {2019},
  pages =        {519--527}
}


@inproceedings{Freedom:2023,
    author = {Zhou, Xin and Shen, Zhiqi},
    title = {A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation},
    year = {2023},
    booktitle = {Proceedings of the 31st ACM International Conference on Multimedia},
    pages = {935–943},
    publisher = {},
    address = {}
}

@inproceedings{BM3:2023,
    author = {Zhou, Xin and Zhou, Hongyu and Liu, Yong and Zeng, Zhiwei and Miao, Chunyan and Wang, Pengwei and You, Yuan and Jiang, Feijun},
    title = {Bootstrap Latent Representations for Multi-Modal Recommendation},
    year = {2023},
    booktitle = {The Web Conference},
    pages = {845–854}
}


@inproceedings{LATTICE:2021,
    author = {Zhang, Jinghao and Zhu, Yanqiao and Liu, Qiang and Wu, Shu and Wang, Shuhui and Wang, Liang},
    title = {Mining Latent Structures for Multimedia Recommendation},
    year = {2021},
    booktitle = {Proceedings of the 29th ACM International Conference on Multimedia},
    pages = {3872–3880}
}


@inproceedings{dicer:2020,
    author = {Zhang, Yin and Zhu, Ziwei and He, Yun and Caverlee, James},
    title = {Content-Collaborative Disentanglement Representation Learning for Enhanced Recommendation},
    year = {2020},
    booktitle = {RecSys},
    pages = {43–52},
    numpages = {10}
}


@inproceedings{MappingDOT:2016,
  author       = {Micha{\"{e}}l Perrot and
                  Nicolas Courty and
                  R{\'{e}}mi Flamary and
                  Amaury Habrard},
  title        = {Mapping Estimation for Discrete Optimal Transport},
  booktitle    = {NeurIPS},
  pages        = {4197--4205},
  year         = {2016}
}


@inproceedings{OT_reglab:2014,
    author = {Courty, Nicolas and Flamary, R\'{e}mi and Tuia, Devis},
    title = {Domain Adaptation with Regularized Optimal Transport},
    year = {2014},
    booktitle = {Machine Learning and Knowledge Discovery in Databases},
    pages = {274–289}
}


@inproceedings{fusion_OT:2020,
  author       = {Sidak Pal Singh and
                  Martin Jaggi},
  title        = {Model Fusion via Optimal Transport},
  booktitle    = {NeurIPS},
    pages = {},
  year         = {2020}
}

@inproceedings{gumbel_softmax:2017,
    title={Categorical Reparameterization with Gumbel-Softmax},
    author={Eric Jang and Shixiang Gu and Ben Poole},
    booktitle={ICLR},
    year={2017}
}

@inproceedings{Concrete_dist:2017,
  author    = {Chris J. Maddison and
               Andriy Mnih and
               Yee Whye Teh},
  title     = {The Concrete Distribution: {A} Continuous Relaxation of Discrete Random Variables},
  year      = {2017},
  booktitle = {ICLR}
}


@inproceedings{BERT:2019,
  author       = {Jacob Devlin and
                  Ming{-}Wei Chang and
                  Kenton Lee and
                  Kristina Toutanova},
  title        = {{BERT:} Pre-training of Deep Bidirectional Transformers for Language
                  Understanding},
  booktitle    = {NAACL},
  pages        = {4171--4186},
  year         = {2019}
}


@ARTICLE{OT_DA:2016,
  author={Courty, Nicolas and Flamary, Rémi and Tuia, Devis and Rakotomamonjy, Alain},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Optimal Transport for Domain Adaptation}, 
  year={2017},
  volume={39},
  number={9},
  pages={1853-1865}
}


@inproceedings{VALID:2023,
    author = {Tran, Nhu-Thuat and Lauw, Hady W.},
    title = {Multi-Representation Variational Autoencoder via Iterative Latent Attention and Implicit Differentiation},
    year = {2023},
    booktitle = {CIKM},
    pages = {2462–2471}
}


@inproceedings{EASEr:2020,
    author = {Jeunen, Olivier and Van Balen, Jan and Goethals, Bart},
    title = {Closed-Form Models for Collaborative Filtering with Side-Information},
    year = {2020},
    booktitle = {RecSys},
    pages = {651–656}
}


@inproceedings{HybridSVD:2019,
    author = {Frolov, Evgeny and Oseledets, Ivan},
    title = {HybridSVD: when collaborative information is not enough},
    year = {2019},
    booktitle = {RecSys},
    pages = {331–339}
}


@inproceedings{FM:2010,
  author       = {Steffen Rendle},
  title        = {Factorization Machines},
  booktitle    = {The 10th {IEEE} ICDM},
  pages        = {995--1000},
  year         = {2010}
}

@inproceedings{FacetVAE:2024,
    author = {Tran, Nhu Thuat and Lauw, Hady W.},
    title={Learning Multi-Faceted Prototypical User Interests},
    year = {2024},
    booktitle = {ICLR}
}

@inproceedings{ELSA:2022,
    author = {Van\v{c}ura, Vojt\v{e}ch and Alves, Rodrigo and Kasalick\'{y}, Petr and Kord\'{\i}k, Pavel},
    title = {Scalable Linear Shallow Autoencoder for Collaborative Filtering},
    year = {2022},
    booktitle = {RecSys},
    pages = {604–609}
}


@inproceedings{UniSRec:2022,
  author = {Yupeng Hou and Shanlei Mu and Wayne Xin Zhao and Yaliang Li and Bolin Ding and Ji-Rong Wen},
  title = {Towards Universal Sequence Representation Learning for Recommender Systems},
  booktitle = {{KDD}},
  year = {2022}
}


@inproceedings{TIGER:2023,
  author       = {Shashank Rajput and
                  Nikhil Mehta and
                  Anima Singh and
                  Raghunandan Hulikal Keshavan and
                  Trung Vu and
                  Lukasz Heldt and
                  Lichan Hong and
                  Yi Tay and
                  Vinh Q. Tran and
                  Jonah Samost and
                  Maciej Kula and
                  Ed H. Chi and
                  Mahesh Sathiamoorthy},
  title        = {Recommender Systems with Generative Retrieval},
  booktitle    = {Advances in Neural Information Processing Systems},
  year         = {2023}
}


@article{DGVAE:2024,
  author       = {Xin Zhou and
                  Chunyan Miao},
  title        = {Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation
                  With Interpretability},
  journal      = {{IEEE} Trans. Multim.},
  volume       = {26},
  pages        = {7543--7554},
  year         = {2024}
}

@article{AlphaRec:2024,
  author       = {Leheng Sheng and
                  An Zhang and
                  Yi Zhang and
                  Yuxin Chen and
                  Xiang Wang and
                  Tat{-}Seng Chua},
  title        = {Language Models Encode Collaborative Signals in Recommendation},
  journal      = {CoRR},
  volume       = {abs/2407.05441},
  year         = {2024},
  url          = {https://doi.org/10.48550/arXiv.2407.05441}
}


@inproceedings{recsys_eval_setting:2020,
    author = {Zhao, Wayne Xin and Chen, Junhua and Wang, Pengfei and Gu, Qi and Wen, Ji-Rong},
    title = {Revisiting Alternative Experimental Settings for Evaluating Top-N Item Recommendation Algorithms},
    year = {2020},
    booktitle = {CIKM},
    pages = {2329–2332}
}


@inproceedings{DualVAE:2024,
  author       = {Zhiqiang Guo and
                  Guohui Li and
                  Jianjun Li and
                  Chaoyang Wang and
                  Si Shi},
  title        = {DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation},
  booktitle    = {SDM},
  pages        = {571--579},
  year         = {2024}
}


@inproceedings{AlignMacridVAE:2024,
  author       = {Ignacio Avas and
                  Liesbeth Allein and
                  Katrien Laenen and
                  Marie{-}Francine Moens},
  title        = {Align MacridVAE: Multimodal Alignment for Disentangled Recommendations},
  booktitle    = {European Conference on Information Retrieval},
  pages        = {73--89},
  year         = {2024}
}


@inproceedings{GOTNet:2022,
    author = {Chen, Huiyuan and Yeh, Chin-Chia Michael and Wang, Fei and Yang, Hao},
    title = {Graph Neural Transport Networks with Non-local Attentions for Recommender Systems},
    year = {2022},
    booktitle = {Proceedings of the ACM Web Conference 2022},
    pages = {1955–1964}
}


@inproceedings{UDMCF:2024,
    author = {Liu, Weiming and Chen, Chaochao and Liao, Xinting and Hu, Mengling and Su, Jiajie and Tan, Yanchao and Wang, Fan},
    title = {User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation},
    year = {2024},
    booktitle = {The Web Conference},
    pages = {334–343}
}


@article{VBAE:2023,
  author       = {Yaochen Zhu and
                  Zhenzhong Chen},
  title        = {Variational Bandwidth Auto-Encoder for Hybrid Recommender Systems},
  journal      = {{IEEE} Trans. Knowl. Data Eng.},
  volume       = {35},
  number       = {5},
  pages        = {5371--5385},
  year         = {2023}
}

@article{MDCF:2023,
  author       = {Yang Xu and
                  Lei Zhu and
                  Zhiyong Cheng and
                  Jingjing Li and
                  Zheng Zhang and
                  Huaxiang Zhang},
  title        = {Multi-Modal Discrete Collaborative Filtering for Efficient Cold-Start
                  Recommendation},
  journal      = {{IEEE} Trans. Knowl. Data Eng.},
  volume       = {35},
  number       = {1},
  pages        = {741--755},
  year         = {2023}
}


@article{ContentRecSurvey:2023,
  author       = {Le Wu and
                  Xiangnan He and
                  Xiang Wang and
                  Kun Zhang and
                  Meng Wang},
  title        = {A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative
                  Filtering to Information-Rich Recommendation},
  journal      = {{IEEE} Trans. Knowl. Data Eng.},
  volume       = {35},
  number       = {5},
  pages        = {4425--4445},
  year         = {2023}
}