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Large Language Models (LLMs) for Recommendation (LLM4Rec) is a promising research direction that has demonstrated exceptional performance in this field.
Session-based recommendations with recurrent neural networks
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Self-Attentive Sequential Recommendation. In IEEE International Conference on Data Mining, ICDM 2018, Singapore, November 17-20, 2018 . IEEE Computer Society, 197–206
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Personalized top-n sequential recommendation via convolutional sequence embedding. In Proceedings of the eleventh ACM international conference on web search and data mining . 565–573
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Deep Interest Network for Click-Through Rate Prediction. In KDD . ACM, 1059–1068
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Improving cold-start recommendation via multi-prior meta-learning. In Advances in Information Retrieval: 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28–April 1, 2021, Proceedings, Part II 43 . Springer, 249–256
Zhengyu Chen, Donglin Wang, and Shiqian Yin. 2021a · 2021
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Device-Cloud Collaborative Learning for Recommendation. In KDD . ACM, 3865–3874
Jiangchao Yao, Feng Wang, Kunyang Jia, Bo Han, Jingren Zhou, and Hongxia Yang. 2021 · 2021
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Mining latent structures for multimedia recommendation. In Proceedings of the 29th ACM international conference on multimedia . 3872–3880
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, Shuhui Wang, and Liang Wang. 2021 · 2021
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Intent contrastive learning for sequential recommendation. In Proceedings of the ACM Web Conference 2022 . 2172–2182
Yongjun Chen, Zhiwei Liu, Jia Li, Julian McAuley, and Caiming Xiong. 2022 · 2022
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Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). In RecSys . ACM, 299–315
Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, and Yongfeng Zhang. 2022 · 2022
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CoRec: an efficient internet behavior-based recommendation framework with edge-cloud collaboration on deep convolution neural networks
Yangfan Li, Kenli Li, Wei Wei, Tianyi Zhou, and Cen Chen. 2022 · 2022
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Intelligent request strategy design in recommender system. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 3772–3782
Xufeng Qian, Yue Xu, Fuyu Lv, Shengyu Zhang, Ziwen Jiang, Qingwen Liu, Xiaoyi Zeng, Tat-Seng Chua, and Fei Wu. 2022 · 2022
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Response generation by jointly modeling personalized linguistic styles and emotions
Teng Sun, Chun Wang, Xuemeng Song, Fuli Feng, and Liqiang Nie. 2022 · 2022
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Device-cloud Collaborative Recommendation via Meta Controller. In KDD . ACM, 4353–4362
Jiangchao Yao, Feng Wang, Xichen Ding, Shaohu Chen, Bo Han, Jingren Zhou, and Hongxia Yang. 2022 · 2022
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Latent structure mining with contrastive modality fusion for multimedia recommendation
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, and Liang Wang. 2022 · 2022
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DDGHM: Dual dynamic graph with hybrid metric training for cross-domain sequential recommendation. In Proceedings of the 30th ACM International Conference on Multimedia . 471–481
Xiaolin Zheng, Jiajie Su, Weiming Liu, and Chaochao Chen. 2022 · 2022
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TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He. 2023a · 2023
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Uncovering ChatGPT’s Capabilities in Recommender Systems. In RecSys . ACM, 1126–1132
Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, and Jun Xu. 2023 · 2023
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End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation. In CAAI International Conference on Artificial Intelligence . Springer, 415–429
Kairui Fu, Qiaowei Miao, Shengyu Zhang, Kun Kuang, and Fei Wu. 2023 · 2023
Cited alongside, same era.
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System
Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, and Peng Jiang. 2023b · 2023
Cited alongside, same era.
Chat-rec: Towards interactive and explainable llms-augmented recommender system
Yunfan Gao, Tao Sheng, Youlin Xiang, Yun Xiong, Haofen Wang, and Jiawei Zhang. 2023a · 2023
Cited alongside, same era.
Genrec: Large language model for generative recommendation
Jianchao Ji, Zelong Li, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Juntao Tan, and Yongfeng Zhang. 2023a · 2023
Cited alongside, same era.
Prompt Distillation for Efficient LLM-based Recommendation. In CIKM . ACM, 1348–1357
Popularity-aware Distributionally Robust Optimization for Recommendation System. In CIKM . ACM, 4967–4973
Jujia Zhao, Wenjie Wang, Xinyu Lin, Leigang Qu, Jizhi Zhang, and Tat-Seng Chua. 2023 · 2023
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DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation. In KDD . ACM, 816–826
Kairui Fu, Shengyu Zhang, Zheqi Lv, Jingyuan Chen, and Jiwei Li. 2024 · 2024
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Tokenpacker: Efficient visual projector for multimodal llm
Wentong Li, Yuqian Yuan, Jian Liu, Dongqi Tang, Song Wang, Jie Qin, Jianke Zhu, and Lei Zhang. 2024 · 2024
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Efficient Inference for Large Language Model-based Generative Recommendation
Xinyu Lin, Chaoqun Yang, Wenjie Wang, Yongqi Li, Cunxiao Du, Fuli Feng, See-Kiong Ng, and Tat-Seng Chua. 2024b · 2024
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Structure-aware Domain Knowledge Injection for Large Language Models
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Lei Li, Yongfeng Zhang, and Li Chen. 2023 · 2023
Cited alongside, same era.
Ppgencdr: A stable and robust framework for privacy-preserving cross-domain recommendation. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 37. 4453–4461
Xinting Liao, Weiming Liu, Xiaolin Zheng, Binhui Yao, and Chaochao Chen. 2023 · 2023
Cited alongside, same era.
Hunter Lightman, Vineet Kosaraju, Yura Burda, Harri Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, and Karl Cobbe. 2023 · 2023
Cited alongside, same era.
Is ChatGPT a Good Recommender? A Preliminary Study
Junling Liu, Chao Liu, Renjie Lv, Kang Zhou, and Yan Zhang. 2023a · 2023
Cited alongside, same era.
Joint internal multi-interest exploration and external domain alignment for cross domain sequential recommendation. In Proceedings of the ACM Web Conference 2023 . 383–394
Weiming Liu, Xiaolin Zheng, Chaochao Chen, Jiajie Su, Xinting Liao, Mengling Hu, and Yanchao Tan. 2023b · 2023
Cited alongside, same era.
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation
Sichun Luo, Bowei He, Haohan Zhao, Yinya Huang, Aojun Zhou, Zongpeng Li, Yuanzhang Xiao, Mingjie Zhan, and Linqi Song. 2023 · 2023
Cited alongside, same era.
DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization. In WWW . ACM, 3077–3085
Zheqi Lv, Wenqiao Zhang, Shengyu Zhang, Kun Kuang, Feng Wang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Beng Chin Ooi, and Fei Wu. 2023 · 2023
Cited alongside, same era.
Enhancing hierarchy-aware graph networks with deep dual clustering for session-based recommendation. In Proceedings of the ACM Web Conference 2023 . 165–176
Jiajie Su, Chaochao Chen, Weiming Liu, Fei Wu, Xiaolin Zheng, and Haoming Lyu. 2023 · 2023
Cited alongside, same era.
Kai Liu, Ze Chen, Zhihang Fu, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, and Jieping Ye. 2024a · 2024
Later among the works it cites.
Enhancing LLM’s Cognition via Structurization
Kai Liu, Zhihang Fu, Chao Chen, Wei Zhang, Rongxin Jiang, Fan Zhou, Yaowu Chen, Yue Wu, and Jieping Ye. 2024c · 2024
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Parrot: Enhancing multi-turn instruction following for large language models. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 9729–9750
Yuchong Sun, Che Liu, Kun Zhou, Jinwen Huang, Ruihua Song, Wayne Xin Zhao, Fuzheng Zhang, Di Zhang, and Kun Gai. 2024 · 2024
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Causal-driven Large Language Models with Faithful Reasoning for Knowledge Question Answering. In Proceedings of the 32nd ACM International Conference on Multimedia . 4331–4340
Jiawei Wang, Da Cao, Shaofei Lu, Zhanchang Ma, Junbin Xiao, and Tat-Seng Chua. 2024 · 2024
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A survey on large language models for recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, and Enhong Chen. 2024b · 2024
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A Study of Implicit Ranking Unfairness in Large Language Models. In EMNLP (Findings) . Association for Computational Linguistics, 7957–7970
Chen Xu, Wenjie Wang, Yuxin Li, Liang Pang, Jun Xu, and Tat-Seng Chua. 2024 · 2024
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Transfr: Transferable federated recommendation with pre-trained language models
Honglei Zhang, He Liu, Haoxuan Li, and Yidong Li. 2024a · 2024
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LLaSA: Large Language and E-Commerce Shopping Assistant. In Amazon KDD Cup 2024 Workshop
Shuo Zhang, Boci Peng, Xinping Zhao, Boren Hu, Yun Zhu, Yanjia Zeng, and Xuming Hu. 2024b · 2024
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Recommender Systems in the Era of Large Language Models (LLMs)
Zihuai Zhao, Wenqi Fan, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Zhen Wen, Fei Wang, Xiangyu Zhao, Jiliang Tang, and Qing Li. 2024a · 2024
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Recommender Systems in the Era of Large Language Models (LLMs)
Zihuai Zhao, Wenqi Fan, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Zhen Wen, Fei Wang, Xiangyu Zhao, Jiliang Tang, and Qing Li. 2024b · 2024
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Efficient Tuning and Inference for Large Language Models on Textual Graphs. In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24 , Kate Larson (Ed.). International Joint Conferences on Artificial Intelligence Organization, 5734–5742
Yun Zhu, Yaoke Wang, Haizhou Shi, and Siliang Tang. 2024b · 2024
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Automated Malware Assembly Line: Uniting Piggybacking and Adversarial Example in Android Malware Generation. In 32nd Annual Network and Distributed System Security Symposium, NDSS 2025, San Diego, California, USA, February 24 - February 28, 2025 . The Internet Society
Heng Li, Zhiyuan Yao, Bang Wu, Cuiying Gao, Teng Xu, Wei Yuan, and Xiapu Luo. 2025 · 2025
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Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations. In KDD . ACM, 2026–2036
Jing Long, Guanhua Ye, Tong Chen, Yang Wang, Meng Wang, and Hongzhi Yin. 2024a · 2036
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Diffusion-based cloud-edge-device collaborative learning for next POI recommendations. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 2026–2036
Jing Long, Guanhua Ye, Tong Chen, Yang Wang, Meng Wang, and Hongzhi Yin. 2024b · 2036
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