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ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction.

J. Lin, B. Chen, H. Wang, Y. Xi, Y. Qu, X. Dai, K. Zhang, R. Tang, Y. Yu, and W. Zhang. CoRR, (2023)

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Tang Tang

Fei Tang

Junhua Tang

Jian Tang

Xinhua Tang

Other publications of authors with the same name

What You Pay for Is What You Get.R. Tang, D. Shao, S. Bressan, and P. Valduriez. DEXA (2), volume 8056 of Lecture Notes in Computer Science, page 395-409. Springer, (2013)The Price Is Right - Models and Algorithms for Pricing Data.R. Tang, H. Wu, Z. Bao, S. Bressan, and P. Valduriez. DEXA (2), volume 8056 of Lecture Notes in Computer Science, page 380-394. Springer, (2013)Learning to Retrieve User Behaviors for Click-through Rate Estimation.J. Qin, W. Zhang, R. Su, Z. Liu, W. Liu, G. Zhao, H. Li, R. Tang, X. He, and Y. Yu. ACM Trans. Inf. Syst., 41 (4): 98:1-98:31 (October 2023)A Unified Framework for Multi-Domain CTR Prediction via Large Language Models.Z. Fu, X. Li, C. Wu, Y. Wang, K. Dong, X. Zhao, M. Zhao, H. Guo, and R. Tang. CoRR, (2023)Collaborative Filtering with Graph-based Implicit Feedback.M. Niu, W. Zhang, Y. Qu, X. Cao, R. Tang, X. He, and Y. Yu. CoRR, (2018)How Can Recommender Systems Benefit from Large Language Models: A Survey.J. Lin, X. Dai, Y. Xi, W. Liu, B. Chen, X. Li, C. Zhu, H. Guo, Y. Yu, R. Tang and 1 other author(s). CoRR, (2023)Towards Automated Negative Sampling in Implicit Recommendation.F. Lyu, Y. Hu, X. Tang, Y. Zhang, R. Tang, and X. Liu. CoRR, (2023)Understanding the planning of LLM agents: A survey.X. Huang, W. Liu, X. Chen, X. Wang, H. Wang, D. Lian, Y. Wang, R. Tang, and E. Chen. CoRR, (2024)Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction.F. Lyu, X. Tang, H. Guo, R. Tang, X. He, R. Zhang, and X. Liu. CoRR, (2021)Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation.H. Wu, Y. Zhang, C. Ma, W. Guo, R. Tang, X. Liu, and M. Coates. CoRR, (2022)

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Disambiguation of "Tang, Ruiming"

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ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction.

Please choose a person to relate this publication to

Tang Tang

Fei Tang

Junhua Tang

Jian Tang

Xinhua Tang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tang, Ruiming"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction.

Please choose a person to relate this publication to

Tang Tang

Fei Tang

Junhua Tang

Jian Tang

Xinhua Tang

Other publications of authors with the same name

Disambiguation

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URL
DOI
BibTeX
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APA
Chicago
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ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction.