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Large Language Models (LLMs) have achieved remarkable success in various fields, prompting several studies to explore their potential in recommendation systems.
Using collaborative filtering to weave an information tapestry
Goldberg, D.; Nichols, D.; Oki, B. M.; and Terry, D. 1992 · 1992
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Item-based collaborative filtering recommendation algorithms
Sarwar, B.; Karypis, G.; Konstan, J.; and Riedl, J. 2001 · 2001
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Matrix factorization techniques for recommender systems
Koren, Y.; Bell, R.; and Volinsky, C. 2009 · 2009
Earlier work this paper cites.
Session-based recommendations with recurrent neural networks
Hidasi, B.; Karatzoglou, A.; Baltrunas, L.; and Tikk, D. 2015 · 2015
Earlier work this paper cites.
Image-based recommendations on styles and substitutes
McAuley, J.; Targett, C.; Shi, Q.; and Van Den Hengel, A. 2015 · 2015
Earlier work this paper cites.
DeepFM: a factorization-machine based neural network for CTR prediction
Guo, H.; Tang, R.; Ye, Y.; Li, Z.; and He, X. 2017 · 2017
Earlier work this paper cites.
Deep & cross network for ad click predictions
Wang, R.; Fu, B.; Fu, G.; and Wang, M. 2017 · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J. 2018 · 2018
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Self-attentive sequential recommendation
Kang, W.-C.; and McAuley, J. 2018 · 2018
Earlier work this paper cites.
Representation learning with contrastive predictive coding
Oord, A. v. d.; Li, Y.; and Vinyals, O. 2018 · 2018
Earlier work this paper cites.
Deep interest network for click-through rate prediction
Zhou, G.; Zhu, X.; Song, C.; Fan, Y.; Zhu, H.; Ma, X.; Yan, Y.; Jin, J.; Li, H.; and Gai, K. 2018 · 2018
Earlier work this paper cites.
BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer
Sun, F.; Liu, J.; Wu, J.; Pei, C.; Lin, X.; Ou, W.; and Jiang, P. 2019 · 2019
Earlier work this paper cites.
Deep interest evolution network for click-through rate prediction
Zhou, G.; Mou, N.; Fan, Y.; Pi, Q.; Bian, W.; Zhou, C.; Zhu, X.; and Gai, K. 2019 · 2019
Earlier work this paper cites.
Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems
Wang, R.; Shivanna, R.; Cheng, D.; Jain, S.; Lin, D.; Hong, L.; and Chi, E. 2021 · 2021
Earlier work this paper cites.
Itemsage: Learning product embeddings for shopping recommendations at pinterest
Baltescu, P.; Chen, H.; Pancha, N.; Zhai, A.; Leskovec, J.; and Rosenberg, C. 2022 · 2022
Cited alongside, same era.
M6-rec: Generative pretrained language models are open-ended recommender systems
Cui, Z.; Ma, J.; Zhou, C.; Zhou, J.; and Yang, H. 2022 · 2022
Cited alongside, same era.
Text and code embeddings by contrastive pre-training
Neelakantan, A.; Xu, T.; Puri, R.; Radford, A.; Han, J. M.; Tworek, J.; Yuan, Q.; Tezak, N.; Kim, J. W.; Hallacy, C.; et al. 2022 · 2022
Cited alongside, same era.
Introducing ChatGPT
OpenAI. 2022 · 2022
Cited alongside, same era.
Achiam, J.; Adler, S.; Agarwal, S.; Ahmad, L.; Akkaya, I.; Aleman, F. L.; Almeida, D.; Altenschmidt, J.; Altman, S.; Anadkat, S.; et al. 2023 · 2023
Towards open-world recommendation with knowledge augmentation from large language models
Xi, Y.; Liu, W.; Lin, J.; Cai, X.; Zhu, H.; Zhu, J.; Chen, B.; Tang, R.; Zhang, W.; Zhang, R.; et al. 2023 · 2023
Later among the works it cites.
Palr: Personalization aware llms for recommendation
Yang, F.; Chen, Z.; Jiang, Z.; Cho, E.; Huang, X.; and Lu, Y. 2023 · 2023
Later among the works it cites.
Knowledge prompt-tuning for sequential recommendation
Zhai, J.; Zheng, X.; Wang, C.-D.; Li, H.; and Tian, Y. 2023 · 2023
Later among the works it cites.
Recommendation as instruction following: A large language model empowered recommendation approach
Zhang, J.; Xie, R.; Hou, Y.; Zhao, W. X.; Lin, L.; and Wen, J.-R. 2023 · 2023
Later among the works it cites.
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Cheng, Y.; Pan, Y.; Zhang, J.; Ni, Y.; Sun, A.; and Yuan, F. 2024 · 2024
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Cited alongside, same era.
Baichuan 2: Open Large-scale Language Models
Baichuan. 2023 · 2023
Cited alongside, same era.
Tallrec: An effective and efficient tuning framework to align large language model with recommendation
Bao, K.; Zhang, J.; Zhang, Y.; Wang, W.; Feng, F.; and He, X. 2023 · 2023
Cited alongside, same era.
Leveraging large language models in conversational recommender systems
Friedman, L.; Ahuja, S.; Allen, D.; Tan, Z.; Sidahmed, H.; Long, C.; Xie, J.; Schubiner, G.; Patel, A.; Lara, H.; et al. 2023 · 2023
Cited alongside, same era.
Do llms understand user preferences? evaluating llms on user rating prediction
Kang, W.-C.; Ni, J.; Mehta, N.; Sathiamoorthy, M.; Hong, L.; Chi, E.; and Cheng, D. Z. 2023 · 2023
Cited alongside, same era.
Scaling law for recommendation models: Towards general-purpose user representations
Shin, K.; Kwak, H.; Kim, S. Y.; Ramström, M. N.; Jeong, J.; Ha, J.-W.; and Kim, K.-M. 2023 · 2023
Cited alongside, same era.
Gemini: a family of highly capable multimodal models
Team, G.; Anil, R.; Borgeaud, S.; Wu, Y.; Alayrac, J.-B.; Yu, J.; Soricut, R.; Schalkwyk, J.; Dai, A. M.; Hauth, A.; et al. 2023 · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models
Touvron, H.; Lavril, T.; Izacard, G.; Martinet, X.; Lachaux, M.-A.; Lacroix, T.; Rozière, B.; Goyal, N.; Hambro, E.; Azhar, F.; et al. 2023 · 2023
Cited alongside, same era.
Closest in time.
Jia, J.; Wang, Y.; Li, Y.; Chen, H.; Bai, X.; Liu, Z.; Liang, J.; Chen, Q.; Li, H.; Jiang, P.; et al. 2024 · 2024
Closest in time.
CALRec: Contrastive Alignment of Generative LLMs For Sequential Recommendation
Li, Y.; Zhai, X.; Alzantot, M.; Yu, K.; Vulić, I.; Korhonen, A.; and Hammad, M. 2024 · 2024
Closest in time.
Llara: Large language-recommendation assistant
Liao, J.; Li, S.; Yang, Z.; Wu, J.; Yuan, Y.; Wang, X.; and He, X. 2024 · 2024
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User-LLM: Efficient LLM Contextualization with User Embeddings
Ning, L.; Liu, L.; Wu, J.; Wu, N.; Berlowitz, D.; Prakash, S.; Green, B.; O’Banion, S.; and Xie, J. 2024 · 2024
Closest in time.
Representation learning with large language models for recommendation
Ren, X.; Wei, W.; Xia, L.; Su, L.; Cheng, S.; Wang, J.; Yin, D.; and Huang, C. 2024 · 2024
Closest in time.
Large Language Models as Data Augmenters for Cold-Start Item Recommendation
Wang, J.; Lu, H.; Caverlee, J.; Chi, E. H.; and Chen, M. 2024 · 2024
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Zhai, J.; Liao, L.; Liu, X.; Wang, Y.; Li, R.; Cao, X.; Gao, L.; Gong, Z.; Gu, F.; He, M.; et al. 2024 · 2024
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Lima: Less is more for alignment
Zhou, C.; Liu, P.; Xu, P.; Iyer, S.; Sun, J.; Mao, Y.; Ma, X.; Efrat, A.; Yu, P.; Yu, L.; et al. 2024 · 2024
Closest in time.