PPM : A Pre-trained Plug-in Model for Click-through Rate Prediction
Fuente:
arXiv
Saved in:
| Main Authors: | Gao, Yuanbo, Lin, Peng, Wang, Dongyue, Mei, Feng, Zhao, Xiwei, Xu, Sulong, Hu, Jinghe |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Hybrid Cross-Stage Coordination Pre-ranking Model for Online Recommendation Systems
by: Zhao, Binglei, et al.
Published: (2025)
by: Zhao, Binglei, et al.
Published: (2025)
A Preference-oriented Diversity Model Based on Mutual-information in Re-ranking for E-commerce Search
by: Wang, Huimu, et al.
Published: (2024)
by: Wang, Huimu, et al.
Published: (2024)
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models
by: Zhang, Kexin, et al.
Published: (2024)
by: Zhang, Kexin, et al.
Published: (2024)
Diffusion-based Multi-modal Synergy Interest Network for Click-through Rate Prediction
by: Cui, Xiaoxi, et al.
Published: (2025)
by: Cui, Xiaoxi, et al.
Published: (2025)
Retrieval-Oriented Knowledge for Click-Through Rate Prediction
by: Liu, Huanshuo, et al.
Published: (2024)
by: Liu, Huanshuo, et al.
Published: (2024)
GRAB: An LLM-Inspired Sequence-First Click-Through Rate Prediction Modeling Paradigm
by: Chen, Shaopeng, et al.
Published: (2026)
by: Chen, Shaopeng, et al.
Published: (2026)
Open Benchmarking for Click-Through Rate Prediction
by: Zhu, Jieming, et al.
Published: (2020)
by: Zhu, Jieming, et al.
Published: (2020)
COINS: SemantiC Ids Enhanced COLd Item RepresentatioN for Click-through Rate Prediction in E-commerce Search
by: Zhao, Qihang, et al.
Published: (2025)
by: Zhao, Qihang, et al.
Published: (2025)
Generative Long-term User Interest Modeling for Click-Through Rate Prediction
by: Shao, Jiangli, et al.
Published: (2026)
by: Shao, Jiangli, et al.
Published: (2026)
Learning Multi-Branch Cooperation for Enhanced Click-Through Rate Prediction at Taobao
by: Chen, Xu, et al.
Published: (2024)
by: Chen, Xu, et al.
Published: (2024)
Distribution-Aware End-to-End Embedding for Streaming Numerical Features in Click-Through Rate Prediction
by: Liu, Jiahao, et al.
Published: (2026)
by: Liu, Jiahao, et al.
Published: (2026)
Addressing Cold-start Problem in Click-Through Rate Prediction via Supervised Diffusion Modeling
by: Zhu, Wenqiao, et al.
Published: (2025)
by: Zhu, Wenqiao, et al.
Published: (2025)
FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction
by: Dai, Zenan, et al.
Published: (2026)
by: Dai, Zenan, et al.
Published: (2026)
Pre-train and Fine-tune: Recommenders as Large Models
by: Jiang, Zhenhao, et al.
Published: (2025)
by: Jiang, Zhenhao, et al.
Published: (2025)
All-domain Moveline Evolution Network for Click-Through Rate Prediction
by: Gao, Chen, et al.
Published: (2024)
by: Gao, Chen, et al.
Published: (2024)
A New Creative Generation Pipeline for Click-Through Rate with Stable Diffusion Model
by: Yang, Hao, et al.
Published: (2024)
by: Yang, Hao, et al.
Published: (2024)
NeSHFS: Neighborhood Search with Heuristic-based Feature Selection for Click-Through Rate Prediction
by: Aksu, Dogukan, et al.
Published: (2024)
by: Aksu, Dogukan, et al.
Published: (2024)
Towards Unifying Feature Interaction Models for Click-Through Rate Prediction
by: Kang, Yu, et al.
Published: (2024)
by: Kang, Yu, et al.
Published: (2024)
Towards Reliable Negative Sampling for Recommendation with Implicit Feedback via In-Community Popularity
by: Chen, Chen, et al.
Published: (2026)
by: Chen, Chen, et al.
Published: (2026)
RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction
by: Li, Yushen, et al.
Published: (2024)
by: Li, Yushen, et al.
Published: (2024)
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
by: Lin, Jianghao, et al.
Published: (2023)
by: Lin, Jianghao, et al.
Published: (2023)
InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction
by: Zeng, Zhichen, et al.
Published: (2024)
by: Zeng, Zhichen, et al.
Published: (2024)
Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models
by: Wang, Yuhao, et al.
Published: (2024)
by: Wang, Yuhao, et al.
Published: (2024)
Understanding and Counteracting Feature-Level Bias in Click-Through Rate Prediction
by: Jin, Jinqiu, et al.
Published: (2024)
by: Jin, Jinqiu, et al.
Published: (2024)
LREF: A Novel LLM-based Relevance Framework for E-commerce
by: Tang, Tian, et al.
Published: (2025)
by: Tang, Tian, et al.
Published: (2025)
Selective Test-Time Compute Scaling for Click-Through Rate Prediction via Uncertainty-Triggered Feature Path Exploration
by: Zhang, Moyu, et al.
Published: (2026)
by: Zhang, Moyu, et al.
Published: (2026)
All-in-One: Heterogeneous Interaction Modeling for Cold-Start Rating Prediction
by: Fang, Shuheng, et al.
Published: (2024)
by: Fang, Shuheng, et al.
Published: (2024)
Adaptive User Interest Modeling via Conditioned Denoising Diffusion For Click-Through Rate Prediction
by: Zhao, Qihang, et al.
Published: (2025)
by: Zhao, Qihang, et al.
Published: (2025)
Deep Pattern Network for Click-Through Rate Prediction
by: Zhang, Hengyu, et al.
Published: (2024)
by: Zhang, Hengyu, et al.
Published: (2024)
Optimizing Feature Set for Click-Through Rate Prediction
by: Lyu, Fuyuan, et al.
Published: (2023)
by: Lyu, Fuyuan, et al.
Published: (2023)
GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation
by: Zou, Yanyan, et al.
Published: (2026)
by: Zou, Yanyan, et al.
Published: (2026)
A Click-Through Rate Prediction Method Based on Cross-Importance of Multi-Order Features
by: Wang, Hao, et al.
Published: (2024)
by: Wang, Hao, et al.
Published: (2024)
GraphPro: Graph Pre-training and Prompt Learning for Recommendation
by: Yang, Yuhao, et al.
Published: (2023)
by: Yang, Yuhao, et al.
Published: (2023)
ELEC: Efficient Large Language Model-Empowered Click-Through Rate Prediction
by: Dong, Rui, et al.
Published: (2025)
by: Dong, Rui, et al.
Published: (2025)
Decoupled Multimodal Fusion for User Interest Modeling in Click-Through Rate Prediction
by: Fan, Alin, et al.
Published: (2025)
by: Fan, Alin, et al.
Published: (2025)
EST: Towards Efficient Scaling Laws in Click-Through Rate Prediction via Unified Modeling
by: Liu, Mingyang, et al.
Published: (2026)
by: Liu, Mingyang, et al.
Published: (2026)
Unified Low-rank Compression Framework for Click-through Rate Prediction
by: Yu, Hao, et al.
Published: (2024)
by: Yu, Hao, et al.
Published: (2024)
Pre-trained Recommender Systems: A Causal Debiasing Perspective
by: Lin, Ziqian, et al.
Published: (2023)
by: Lin, Ziqian, et al.
Published: (2023)
Quadratic Interest Network for Multimodal Click-Through Rate Prediction
by: Li, Honghao, et al.
Published: (2025)
by: Li, Honghao, et al.
Published: (2025)
Pre-training Generative Recommender with Multi-Identifier Item Tokenization
by: Zheng, Bowen, et al.
Published: (2025)
by: Zheng, Bowen, et al.
Published: (2025)
Similar Items
-
A Hybrid Cross-Stage Coordination Pre-ranking Model for Online Recommendation Systems
by: Zhao, Binglei, et al.
Published: (2025) -
A Preference-oriented Diversity Model Based on Mutual-information in Re-ranking for E-commerce Search
by: Wang, Huimu, et al.
Published: (2024) -
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models
by: Zhang, Kexin, et al.
Published: (2024) -
Diffusion-based Multi-modal Synergy Interest Network for Click-through Rate Prediction
by: Cui, Xiaoxi, et al.
Published: (2025) -
Retrieval-Oriented Knowledge for Click-Through Rate Prediction
by: Liu, Huanshuo, et al.
Published: (2024)