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Recent advancements in diffusion models have shown promising results in sequential recommendation (SR).
S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. In CIKM ’20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020 . ACM, 1893–1902
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S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. In The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020 . ACM, 1893–1902
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S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. In The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020 . ACM, 1893–1902
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Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation. In IEEE 16th International Conference on Data Mining, December 12-15, 2016, Barcelona, Spain . IEEE Computer Society, 191–200
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Recurrent Neural Networks with Top-k Gains for Session-based Recommendations. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018 . ACM, 843–852
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Self-Attentive Sequential Recommendation. In IEEE International Conference on Data Mining, Singapore, November 17-20, 2018 . IEEE Computer Society, 197–206
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A Collaborative Session-based Recommendation Approach with Parallel Memory Modules. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France, July 21-25, 2019 . ACM, 345–354
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Sequential Recommender Systems: Challenges, Progress and Prospects. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, Macao, China, August 10-16, 2019 . 6332–6338
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A Simple Convolutional Generative Network for Next Item Recommendation. In Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, Melbourne, VIC, Australia, February 11-15, 2019 . ACM, 582–590
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Denoising Diffusion Probabilistic Models. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual
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Diffusion Models Beat GANs on Image Synthesis. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual . 8780–8794
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DiffWave: A Versatile Diffusion Model for Audio Synthesis. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021
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DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023
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Improving Diffusion-Based Image Synthesis with Context Prediction. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023
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Wayne Xin Zhao, Shanlei Mu, Yupeng Hou, Zihan Lin, Yushuo Chen, Xingyu Pan, Kaiyuan Li, Yujie Lu, Hui Wang, Changxin Tian, Yingqian Min, Zhichao Feng, Xinyan Fan, Xu Chen, Pengfei Wang, Wendi Ji, Yaliang Li, Xiaoling Wang, and Ji-Rong Wen. 2021 · 2021
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Intent Contrastive Learning for Sequential Recommendation. In The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022 . ACM, 2172–2182
Yongjun Chen, Zhiwei Liu, Jia Li, Julian J. McAuley, and Caiming Xiong. 2022a · 2022
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Intent Contrastive Learning for Sequential Recommendation. In WWW ’22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022 . ACM, 2172–2182
Yongjun Chen, Zhiwei Liu, Jia Li, Julian J. McAuley, and Caiming Xiong. 2022b · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans. 2022a · 2022
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Classifier-Free Diffusion Guidance
Jonathan Ho and Tim Salimans. 2022b · 2022
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Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, and Tatsunori B. Hashimoto. 2022 · 2022
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Understanding Diffusion Models: A Unified Perspective
Calvin Luo. 2022 · 2022
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SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon. 2022 · 2022
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Hierarchical Text-Conditional Image Generation with CLIP Latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022 · 2022
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Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023
Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, and Xiangnan He. 2023b · 2023
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Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023
Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, and Jun Zhu. 2023 · 2023
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DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models
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DiffuRec: A Diffusion Model for Sequential Recommendation
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A Survey on Diffusion Models for Recommender Systems
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Discrete Conditional Diffusion for Reranking in Recommendation. In Companion Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, Singapore, May 13-17, 2024 . ACM, 161–169
Xiao Lin, Xiaokai Chen, Chenyang Wang, Hantao Shu, Linfeng Song, Biao Li, and Peng Jiang. 2024a · 2024
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SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024
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Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 . ACM, 882–890
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