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Involving collaborative information in Large Language Models (LLMs) is a promising technique for adapting LLMs for recommendation.
BPR: Bayesian Personalized Ranking from Implicit Feedback
Rendle, S.; Freudenthaler, C.; Gantner, Z.; and Schmidt-Thieme, L. 2009 · 2009
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Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2014 · 2014
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TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings
Guo, G.; Zhang, J.; and Yorke-Smith, N. 2015 · 2015
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Image-Based Recommendations on Styles and Substitutes
McAuley, J.; Targett, C.; Shi, Q.; and van den Hengel, A. 2015 · 2015
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Neural Collaborative Filtering
He, X.; Liao, L.; Zhang, H.; Nie, L.; Hu, X.; and Chua, T.-S. 2017 · 2017
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Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2017 · 2017
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Attention is All you Need
Vaswani, A.; Shazeer, N. M.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L.; and Polosukhin, I. 2017 · 2017
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Self-Attentive Sequential Recommendation
Kang, W.-C.; and McAuley, J. 2018 · 2018
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Narayan, S.; Cohen, S. B.; and Lapata, M. 2018 · 2018
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Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
Tang, J.; and Wang, K. 2018 · 2018
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Assessing The Factual Accuracy of Generated Text
Goodrich, B.; Rao, V.; Liu, P. J.; and Saleh, M. 2019 · 2019
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Social IQa: Commonsense Reasoning about Social Interactions
Sap, M.; Rashkin, H.; Chen, D.; Le Bras, R.; and Choi, Y. 2019 · 2019
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LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
He, X.; Deng, K.; Wang, X.; Li, Y.; Zhang, Y.; and Wang, M. 2020 · 2020
Cited alongside, same era.
Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation
Liu, Y.; Liu, Q.; Tian, Y.; Wang, C.; Niu, Y.; Song, Y.; and Li, C. 2021 · 2021
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.
LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2022 · 2022
Cited alongside, same era.
Personalized Prompt Learning for Explainable Recommendation
Li, L.; Zhang, Y.; and Chen, L. 2022 · 2022
Cited alongside, same era.
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning
Large Language Model Augmented Narrative Driven Recommendations
Mysore, S.; McCallum, A.; and Zamani, H. 2023 · 2023
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Recommender Systems with Generative Retrieval
Rajput, S.; Mehta, N.; Singh, A.; Keshavan, R. H.; Vu, T. H.; Heldt, L.; Hong, L.; Tay, Y.; Tran, V. Q.; Samost, J.; Kula, M.; Chi, E. H.; and Sathiamoorthy, M. 2023 · 2023
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Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models
Wang, X.; Tang, X.; Zhao, W. X.; Wang, J.; and rong Wen, J. 2023 · 2023
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Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited
Yuan, Z.; Yuan, F.; Song, Y.; Li, Y.; Fu, J.; Yang, F.; Pan, Y.; and Ni, Y. 2023 · 2023
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CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation
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Wang, X.; Zhou, K.; rong Wen, J.; and Zhao, W. X. 2022 · 2022
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.
Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
Chiang, W.-L.; Li, Z.; Lin, Z.; Sheng, Y.; Wu, Z.; Zhang, H.; Zheng, L.; Zhuang, S.; Zhuang, Y.; Gonzalez, J. E.; Stoica, I.; and Xing, E. P. 2023 · 2023
Cited alongside, same era.
Large Language Models are Zero-Shot Rankers for Recommender Systems
Hou, Y.; Zhang, J.; Lin, Z.; Lu, H.; Xie, R.; McAuley, J.; and Zhao, W. X. 2023 · 2023
Cited alongside, same era.
How to Index Item IDs for Recommendation Foundation Models
Hua, W.; Xu, S.; Ge, Y.; and Zhang, Y. 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. H.; and Cheng, D. Z. 2023 · 2023
Cited alongside, same era.
LLaRA: Large Language-Recommendation Assistant
Liao, J.; Li, S.; Yang, Z.; Wu, J.; Yuan, Y.; Wang, X.; and He, X. 2023 · 2023
Cited alongside, same era.
Zhang, Y.; Feng, F.; Zhang, J.; Bao, K.; Wang, Q.; and He, X. 2023 · 2023
Later among the works it cites.
Prompt Learning for News Recommendation
Zhang, Z.; and wei Wang, B. 2023 · 2023
Later among the works it cites.
A Survey of Large Language Models
Zhao, W. X.; Zhou, K.; Li, J.; Tang, T.; Wang, X.; Hou, Y.; Min, Y.; Zhang, B.; Zhang, J.; Dong, Z.; Du, Y.; Yang, C.; Chen, Y.; Chen, Z.; Jiang, J.; Ren, R.; Li, Y.; Tang, X.; Liu, Z.; Liu, P.; Nie, J.-Y.; and Wen, J.-R. 2023 · 2023
Later among the works it cites.
The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models
Li, J.; Chen, J.; Ren, R.; Cheng, X.; Zhao, W. X.; Nie, J.-Y.; and Wen, J.-R. 2024 · 2024
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Visual Perception by Large Language Model’s Weights
Ma, F.; Xue, H.; Wang, G.; Zhou, Y.; Rao, F.; Yan, S.; Zhang, Y.; Wu, S.; Shou, M. Z.; and Sun, X. 2024 · 2024
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Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation
Zheng, B.; Hou, Y.; Lu, H.; Chen, Y.; Zhao, W. X.; and rong Wen, J. 2023 · 2024
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Harnessing Large Language Models for Text-Rich Sequential Recommendation
Zheng, Z.; Chao, W.; Qiu, Z.; Zhu, H.; and Xiong, H. 2024 · 2024
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