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Recently, Foundation Models (FMs), with their extensive knowledge bases and complex architectures, have offered unique opportunities within the realm of recommender systems (RSs).
Recommender systems: Introduction and challenges
Francesco Ricci, Lior Rokach, and Bracha Shapira · 2015
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What to do next: Modeling user behaviors by time-lstm
Yu Zhu, Hao Li, Yikang Liao, Beidou Wang, Ziyu Guan, Haifeng Liu, and Deng Cai · 2017
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Conversational recommender system
Yueming Sun and Yi Zhang · 2018
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Recsim: A configurable simulation platform for recommender systems
Eugene Ie, Chih-Wei Hsu, Martin Mladenov, Vihan Jain, Sanmit Narvekar, Jing Wang, Rui Wu, and Craig Boutilier · 2019
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Reformer: The efficient transformer
Nikita Kitaev, Lukasz Kaiser, and Anselm Levskaya · 2019
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Deep learning based recommender system: A survey and new perspectives
Shuai Zhang, Lina Yao, Aixin Sun, and Yi Tay · 2019
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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The lottery ticket hypothesis for pre-trained BERT networks
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, and Michael Carbin · 2020
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Span selection pre-training for question answering
Michael R. Glass, Alfio Gliozzo, Rishav Chakravarti, Anthony Ferritto, Lin Pan, G. P. Shrivatsa Bhargav, Dinesh Garg, and Avirup Sil · 2020
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Tinybert: Distilling BERT for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu · 2020
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Estimation-action-reflection: Towards deep interaction between conversational and recommender systems
Wenqiang Lei, Xiangnan He, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan, and Tat-Seng Chua · 2020
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Generate neural template explanations for recommendation
Lei Li, Yongfeng Zhang, and Li Chen · 2020
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Ptum: Pre-training user model from unlabeled user behaviors via self-supervision
Chuhan Wu, Fangzhao Wu, Tao Qi, Jianxun Lian, Yongfeng Huang, and Xing Xie · 2020
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Explainable recommendation: A survey and new perspectives
Yongfeng Zhang and Xu Chen · 2020
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Explainable recommendation: A survey and new perspectives
Yongfeng Zhang, Xu Chen, et al · 2020
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Improving conversational recommender systems via knowledge graph based semantic fusion
Kun Zhou, Wayne Xin Zhao, Shuqing Bian, Yuanhang Zhou, Ji-Rong Wen, and Jingsong Yu · 2020
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, and et al · 2021
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Hao Ding, Yifei Ma, Anoop Deoras, Yuyang Wang, and Hao Wang · 2021
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Advances and challenges in conversational recommender systems: A survey
Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, and Tat-Seng Chua · 2021
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Lingzhi Wang, Huang Hu, Lei Sha, Can Xu, Kam-Fai Wong, and Daxin Jiang · 2021
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Cross-domain recommendation: Challenges, progress, and prospects
Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, and Guanfeng Liu · 2021
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Recommendation unlearning
Chong Chen, Fei Sun, Min Zhang, and Bolin Ding · 2022
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M6-rec: Generative pretrained language models are open-ended recommender systems
Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou, and Hongxia Yang · 2022
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Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5)
Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, and Yongfeng Zhang · 2022
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Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
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A survey on conversational recommender systems
Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, and Li Chen · 2022
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Autotransition: Learning to recommend video transition effects
Yaojie Shen, Libo Zhang, Kai Xu, and Xiaojie Jin · 2022
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Personalized prompts for sequential recommendation
Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, and Qing He · 2022
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Clip-actor: Text-driven recommendation and stylization for animating human meshes
Kim Youwang, Ji-Yeon Kim, and Tae-Hyun Oh · 2022
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A bi-step grounding paradigm for large language models in recommendation systems
Keqin Bao, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yancheng Luo, Fuli Feng, Xiangnan He, and Qi Tian · 2023
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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 · 2023
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Large language models for recommendation: Progresses and future directions
Keqin Bao, Jizhi Zhang, Yang Zhang, Wang Wenjie, Fuli Feng, and Xiangnan He · 2023
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Instruction mining: High-quality instruction data selection for large language models
Yihan Cao, Yanbin Kang, and Lichao Sun · 2023
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Maybe only 0.5% data is needed: A preliminary exploration of low training data instruction tuning
Hao Chen, Yiming Zhang, Qi Zhang, Hantao Yang, Xiaomeng Hu, Xuetao Ma, Yifan Yanggong, and Junbo Zhao · 2023
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Uncovering chatgpt’s capabilities in recommender systems
Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, and Jun Xu · 2023
Earlier work this paper cites.
Attack prompt generation for red teaming and defending large language models
Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, and Xiangnan He · 2023
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Recommender systems in the era of large language models (llms)
Wenqi Fan, Zihuai Zhao, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Jiliang Tang, and Qing Li · 2023
Cited alongside, same era.
Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, and Yunzhu Pan · 2023
Cited alongside, same era.
A unified framework for multi-domain CTR prediction via large language models
Zichuan Fu, Xiangyang Li, Chuhan Wu, Yichao Wang, Kuicai Dong, Xiangyu Zhao, Mengchen Zhao, Huifeng Guo, and Ruiming Tang · 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 · 2023
Cited alongside, same era.
Learning to compress prompts with gist tokens
Jesse Mu, Xiang Lisa Li, and Noah D. Goodman · 2023
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Gpt-4 technical report
OpenAI · 2023
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Logic-scaffolding: Personalized aspect-instructed recommendation explanation generation using llms
Behnam Rahdari, Hao Ding, Ziwei Fan, Yifei Ma, Zhuotong Chen, Anoop Deoras, and Branislav Kveton · 2023
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Outfittransformer: Learning outfit representations for fashion recommendation
Rohan Sarkar, Navaneeth Bodla, Mariya I. Vasileva, Yen-Liang Lin, Anurag Beniwal, Alan Lu, and Gerard Medioni · 2023
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A survey of reasoning with foundation models
Jiankai Sun, Chuanyang Zheng, and et al · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Qianyu Guo, Meng Wang, and Haofen Wang · 2023
Cited alongside, same era.
Vip5: Towards multimodal foundation models for recommendation
Shijie Geng, Juntao Tan, Shuchang Liu, Zuohui Fu, and Yongfeng Zhang · 2023
Cited alongside, same era.
An unified search and recommendation foundation model for cold-start scenario
Yuqi Gong, Xichen Ding, Yehui Su, Kaiming Shen, Zhongyi Liu, and Guannan Zhang · 2023
Cited alongside, same era.
Large language models are zero-shot time series forecasters
Nate Gruver, Marc Anton Finzi, Shikai Qiu, and Andrew Gordon Wilson · 2023
Cited alongside, same era.
Leveraging large language models for sequential recommendation
Jesse Harte, Wouter Zorgdrager, Panos Louridas, Asterios Katsifodimos, Dietmar Jannach, and Marios Fragkoulis · 2023
Cited alongside, same era.
Large language models as zero-shot conversational recommenders
Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, and Julian J. McAuley · 2023
Cited alongside, same era.
Learning vector-quantized item representation for transferable sequential recommenders
Yupeng Hou, Zhankui He, Julian McAuley, and Wayne Xin Zhao · 2023
Cited alongside, same era.
Large language models are zero-shot rankers for recommender systems
Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, and Wayne Xin Zhao · 2023
Cited alongside, same era.
One model for all: Large language models are domain-agnostic recommendation systems
Zuoli Tang, Zhaoxin Huan, Zihao Li, Xiaolu Zhang, Jun Hu, Chilin Fu, Jun Zhou, and Chenliang Li · 2023
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Missrec: Pre-training and transferring multi-modal interest-aware sequence representation for recommendation
Jinpeng Wang, Ziyun Zeng, Yunxiao Wang, Yuting Wang, Xingyu Lu, Tianxiang Li, Jun Yuan, Rui Zhang, Hai-Tao Zheng, and Shu-Tao Xia · 2023
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Recagent: A novel simulation paradigm for recommender systems, 2023
Lei Wang, Jingsen Zhang, Xu Chen, Yankai Lin, Ruihua Song, Wayne Xin Zhao, and Ji-Rong Wen · 2023
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Rethinking the evaluation for conversational recommendation in the era of large language models
Xiaolei Wang, Xinyu Tang, Wayne Xin Zhao, Jingyuan Wang, and Ji-Rong Wen · 2023
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Enhancing recommender systems with large language model reasoning graphs
Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Y. Zhang, Qing Cui, Longfei Li, Jun Zhou, and Sheng Li · 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
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DRDT: dynamic reflection with divergent thinking for llm-based sequential recommendation
Yu Wang, Zhiwei Liu, Jianguo Zhang, Weiran Yao, Shelby Heinecke, and Philip S. Yu · 2023
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Aligning large language models with human: A survey
Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, and Qun Liu · 2023
Later among the works it cites.
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 · 2023
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Towards open-world recommendation with knowledge augmentation from large language models
Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, and Yong Yu · 2023
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Data selection for language models via importance resampling
Sang Michael Xie, Shibani Santurkar, Tengyu Ma, and Percy Liang · 2023
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Cvalues: Measuring the values of chinese large language models from safety to responsibility
Guohai Xu, Jiayi Liu, Ming Yan, Haotian Xu, Jinghui Si, Zhuoran Zhou, Peng Yi, Xing Gao, Jitao Sang, Rong Zhang, Ji Zhang, Chao Peng, Fei Huang, and Jingren Zhou · 2023
Later among the works it cites.
Openp5: Benchmarking foundation models for recommendation
Shuyuan Xu, Wenyue Hua, and Yongfeng Zhang · 2023
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Knowledge plugins: Enhancing large language models for domain-specific recommendations
Jing Yao, Wei Xu, Jianxun Lian, Xiting Wang, Xiaoyuan Yi, and Xing Xie · 2023
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Untargeted attack against federated recommendation systems via poisonous item embeddings and the defense
Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, and Zaixi Zhang · 2023
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Where to go next for recommender systems? ID- vs. modality-based recommender models revisited
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni · 2023
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Knowledge prompt-tuning for sequential recommendation
Jianyang Zhai, Xiawu Zheng, Chang-Dong Wang, Hui Li, and Yonghong Tian · 2023
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Prompt learning for news recommendation
Zizhuo Zhang and Bang Wang · 2023
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On generative agents in recommendation
An Zhang, Leheng Sheng, Yuxin Chen, Hao Li, Yang Deng, Xiang Wang, and Tat-Seng Chua · 2023
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Interactive interior design recommendation via coarse-to-fine multimodal reinforcement learning
He Zhang, Ying Sun, Weiyu Guo, Yafei Liu, Haonan Lu, Xiaodong Lin, and Hui Xiong · 2023
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Is chatgpt fair for recommendation? evaluating fairness in large language model recommendation
Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He · 2023
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Agentcf: Collaborative learning with autonomous language agents for recommender systems
Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun, Julian J. McAuley, Wayne Xin Zhao, Leyu Lin, and Ji-Rong Wen · 2023
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Recommendation as instruction following: A large language model empowered recommendation approach
Junjie Zhang, Ruobing Xie, Yupeng Hou, Wayne Xin Zhao, Leyu Lin, and Ji-Rong Wen · 2023
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User-centric conversational recommendation: Adapting the need of user with large language models
Gangyi Zhang · 2023
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LIMA: less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, and Omer Levy · 2023
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Exploring recommendation capabilities of gpt-4v(ision): A preliminary case study
Peilin Zhou, Meng Cao, You-Liang Huang, Qichen Ye, Peiyan Zhang, Junling Liu, Yueqi Xie, Yining Hua, and Jaeboum Kim · 2023
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Collaborative large language model for recommender systems
Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, and Jundong Li · 2023
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Agent ai: Surveying the horizons of multimodal interaction
Zane Durante, Qiuyuan Huang, Naoki Wake, Ran Gong, Jae Sung Park, Bidipta Sarkar, Rohan Taori, Yusuke Noda, Demetri Terzopoulos, Yejin Choi, et al · 2024
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Chatgpt for conversational recommendation: Refining recommendations by reprompting with feedback
Kyle Dylan Spurlock, Cagla Acun, Esin Saka, and Olfa Nasraoui · 2024
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Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu · 2024
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Lanling Xu, Junjie Zhang, Bingqian Li, Jinpeng Wang, Mingchen Cai, Wayne Xin Zhao, and Ji-Rong Wen · 2024
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