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Traditional recommender systems usually take the user-platform paradigm, where users are directly exposed under the control of the platform's recommendation algorithms.
Fine-grained spoiler detection from large-scale review corpora
Mengting Wan, Rishabh Misra, Ndapa Nakashole, and Julian McAuley. 2019 · 1905
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Item-based collaborative filtering recommendation algorithms
Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 2001 · 2001
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Cumulated gain-based evaluation of ir techniques
Kalervo Järvelin and Jaana Kekäläinen. 2002 · 2002
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
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Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu, and Shaoping Ma. 2014 · 2014
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Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness
Elizabeth Aguirre, Dominik Mahr, Dhruv Grewal, Ko De Ruyter, and Martin Wetzels. 2015 · 2015
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Exposure to ideologically diverse news and opinion on facebook
Eytan Bakshy, Solomon Messing, and Lada A Adamic. 2015 · 2015
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Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2015 · 2015
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Wide & deep learning for recommender systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et al. 2016 · 2016
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Diversity, serendipity, novelty, and coverage: a survey and empirical analysis of beyond-accuracy objectives in recommender systems
Marius Kaminskas and Derek Bridge. 2016 · 2016
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Diversity in recommender systems–a survey
Matevž Kunaver and Tomaž Požrl. 2017 · 2017
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Attention is all you need
A Vaswani. 2017 · 2017
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Maximizing the diversity of exposure in a social network
Cigdem Aslay, Antonis Matakos, Esther Galbrun, and Aristides Gionis. 2018 · 2018
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How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
Allison JB Chaney, Brandon M Stewart, and Barbara E Engelhardt. 2018 · 2018
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Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship
Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, and Michael Mathioudakis. 2018 · 2018
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Self-attentive sequential recommendation
Wang-Cheng Kang and Julian McAuley. 2018 · 2018
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Conversational recommender system
Yueming Sun and Yi Zhang. 2018 · 2018
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Personalizing dialogue agents: I have a dog, do you have pets too
Saizheng Zhang. 2018 · 2018
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Towards conversational search and recommendation: System ask, user respond
Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W Bruce Croft. 2018 · 2018
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Drn: A deep reinforcement learning framework for news recommendation
Guanjie Zheng, Fuzheng Zhang, Zihan Zheng, Yang Xiang, Nicholas Jing Yuan, Xing Xie, and Zhenhui Li. 2018 · 2018
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Deep interest network for click-through rate prediction
Guorui Zhou, Xiaoqiang Zhu, Chenru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, and Kun Gai. 2018 · 2018
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Degenerate feedback loops in recommender systems
Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, and Pushmeet Kohli. 2019 · 2019
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Multi-interest network with dynamic routing for recommendation at tmall
Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Huan Zhao, Pipei Huang, Guoliang Kang, Qiwei Chen, Wei Li, and Dik Lun Lee. 2019 · 2019
Cited alongside, same era.
Justifying recommendations using distantly-labeled reviews and fine-grained aspects
Jianmo Ni, Jiacheng Li, and Julian McAuley. 2019 · 2019
Cited alongside, same era.
Bert with history answer embedding for conversational question answering
Chen Qu, Liu Yang, Minghui Qiu, W Bruce Croft, Yongfeng Zhang, and Mohit Iyyer. 2019 · 2019
Cited alongside, same era.
Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang. 2019 · 2019
Cited alongside, same era.
Deep interest evolution network for click-through rate prediction
Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, and Kun Gai. 2019 · 2019
Cited alongside, same era.
Leveraging large language models in conversational recommender systems
Luke Friedman, Sameer Ahuja, David Allen, Zhenning Tan, Hakim Sidahmed, Changbo Long, Jun Xie, Gabriel Schubiner, Ajay Patel, Harsh Lara, et al. 2023 · 2023
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Recommender Systems, Manipulation and Private Autonomy: How European Civil Law Regulates and Should Regulate Recommender Systems for the Benefit of Private Autonomy , pages 101–128
Karina Grisse. 2023 · 2023
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A real-world webagent with planning, long context understanding, and program synthesis
Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, and Aleksandra Faust. 2023 · 2023
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Xinhang Li, Chong Chen, Xiangyu Zhao, Yong Zhang, and Chunxiao Xing. 2023 · 2023
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Analyzing the impact of filter bubbles on social network polarization
Uthsav Chitra and Christopher Musco. 2020 · 2020
Cited alongside, same era.
Fairecsys: mitigating algorithmic bias in recommender systems
Bora Edizel, Francesco Bonchi, Sara Hajian, André Panisson, and Tamir Tassa. 2020 · 2020
Cited alongside, same era.
Understanding echo chambers in e-commerce recommender systems
Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, and Yongfeng Zhang. 2020 · 2020
Cited alongside, same era.
Do not blame it on the algorithm: an empirical assessment of multiple recommender systems and their impact on content diversity
Judith Möller, Damian Trilling, Natali Helberger, and Bram van Es. 2020 · 2020
Cited alongside, same era.
Fairrec: Two-sided fairness for personalized recommendations in two-sided platforms
Gourab K Patro, Arpita Biswas, Niloy Ganguly, Krishna P Gummadi, and Abhijnan Chakraborty. 2020 · 2020
Cited alongside, same era.
Kerl: A knowledge-guided reinforcement learning model for sequential recommendation
Pengfei Wang, Yu Fan, Long Xia, Wayne Xin Zhao, ShaoZhang Niu, and Jimmy Huang. 2020 · 2020
Cited alongside, same era.
Advances and challenges in conversational recommender systems: A survey
Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, and Tat-Seng Chua. 2021 · 2021
Cited alongside, same era.
Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein. 2023 · 2023
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Role play with large language models
Murray Shanahan, Kyle McDonell, and Laria Reynolds. 2023 · 2023
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Recmind: Large language model powered agent for recommendation
Yancheng Wang, Ziyan Jiang, Zheng Chen, Fan Yang, Yingxue Zhou, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, and Yingzhen Yang. 2023 · 2023
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C-pack: Packaged resources to advance general chinese embedding
Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff. 2023 · 2023
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Neural node matching for multi-target cross domain recommendation
Wujiang Xu, Shaoshuai Li, Mingming Ha, Xiaobo Guo, Qiongxu Ma, Xiaolei Liu, Linxun Chen, and Zhenfeng Zhu. 2023 · 2023
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Phi-3 technical report: A highly capable language model locally on your phone
Marah Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat Behl, et al. 2024 · 2024
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Scaling synthetic data creation with 1,000,000,000 personas
Xin Chan, Xiaoyang Wang, Dian Yu, Haitao Mi, and Dong Yu. 2024 · 2024
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Mind2web: Towards a generalist agent for the web
Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Sam Stevens, Boshi Wang, Huan Sun, and Yu Su. 2024 · 2024
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Apple intelligence foundation language models
Tom Gunter, Zirui Wang, Chong Wang, Ruoming Pang, Andy Narayanan, Aonan Zhang, Bowen Zhang, Chen Chen, Chung-Cheng Chiu, David Qiu, et al. 2024 · 2024
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Easyrec: Simple yet effective language models for recommendation
Xubin Ren and Chao Huang. 2024 · 2024
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Gemma: Open models based on gemini research and technology
Gemma Team, Thomas Mesnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, et al. 2024 · 2024
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Macrec: A multi-agent collaboration framework for recommendation
Zhefan Wang, Yuanqing Yu, Wendi Zheng, Weizhi Ma, and Min Zhang. 2024 · 2024
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Travelplanner: A benchmark for real-world planning with language agents
Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, and Yu Su. 2024 · 2024
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Slmrec: Empowering small language models for sequential recommendation
Wujiang Xu, Zujie Liang, Jiaojiao Han, Xuying Ning, Wenfang Lin, Linxun Chen, Feng Wei, and Yongfeng Zhang. 2024 · 2024
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Jiaqi Zhai, Lucy Liao, Xing Liu, Yueming Wang, Rui Li, Xuan Cao, Leon Gao, Zhaojie Gong, Fangda Gu, Michael He, et al. 2024 · 2024
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Agentcf: Collaborative learning with autonomous language agents for recommender systems
Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun, Julian McAuley, Wayne Xin Zhao, Leyu Lin, and Ji-Rong Wen. 2024b · 2024
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Let me do it for you: Towards llm empowered recommendation via tool learning
Yuyue Zhao, Jiancan Wu, Xiang Wang, Wei Tang, Dingxian Wang, and Maarten de Rijke. 2024 · 2024
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