TF4CTR: Twin Focus Framework for CTR Prediction via Adaptive Sample Differentiation
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Honghao, Ru, Qiuze, Zhang, Yiwen, Zhang, Yi, Sang, Lei, Yang, Yun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Feature Interaction Fusion Self-Distillation Network For CTR Prediction
by: Sang, Lei, et al.
Published: (2024)
by: Sang, Lei, et al.
Published: (2024)
CETN: Contrast-enhanced Through Network for CTR Prediction
by: Li, Honghao, et al.
Published: (2023)
by: Li, Honghao, et al.
Published: (2023)
Enhancing CTR Prediction through Sequential Recommendation Pre-training: Introducing the SRP4CTR Framework
by: Han, Ruidong, et al.
Published: (2024)
by: Han, Ruidong, et al.
Published: (2024)
Explainable CTR Prediction via LLM Reasoning
by: Yu, Xiaohan, et al.
Published: (2024)
by: Yu, Xiaohan, et al.
Published: (2024)
MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths
by: Zhang, Moyu, et al.
Published: (2025)
by: Zhang, Moyu, et al.
Published: (2025)
MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction
by: Yang, Zhiming, et al.
Published: (2024)
by: Yang, Zhiming, et al.
Published: (2024)
A Universal Framework for Compressing Embeddings in CTR Prediction
by: Wang, Kefan, et al.
Published: (2025)
by: Wang, Kefan, et al.
Published: (2025)
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising
by: Yang, Yang, et al.
Published: (2024)
by: Yang, Yang, et al.
Published: (2024)
A Collaborative Ensemble Framework for CTR Prediction
by: Liu, Xiaolong, et al.
Published: (2024)
by: Liu, Xiaolong, et al.
Published: (2024)
Towards An Efficient LLM Training Paradigm for CTR Prediction
by: Lin, Allen, et al.
Published: (2025)
by: Lin, Allen, et al.
Published: (2025)
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)
From Collapse to Stability: A Knowledge-Driven Ensemble Framework for Scaling Up Click-Through Rate Prediction Models
by: Li, Honghao, et al.
Published: (2024)
by: Li, Honghao, et al.
Published: (2024)
MARS: Modality-Aligned Retrieval for Sequence Augmented CTR Prediction
by: Xiao, Yutian, et al.
Published: (2025)
by: Xiao, Yutian, et al.
Published: (2025)
DGenCTR: Towards a Universal Generative Paradigm for Click-Through Rate Prediction via Discrete Diffusion
by: Zhang, Moyu, et al.
Published: (2025)
by: Zhang, Moyu, et al.
Published: (2025)
Discrete Semantic Tokenization for Deep CTR Prediction
by: Liu, Qijiong, et al.
Published: (2024)
by: Liu, Qijiong, et al.
Published: (2024)
A Unified Framework for Multi-Domain CTR Prediction via Large Language Models
by: Fu, Zichuan, et al.
Published: (2023)
by: Fu, Zichuan, et al.
Published: (2023)
A Comprehensive Summarization and Evaluation of Feature Refinement Modules for CTR Prediction
by: Wang, Fangye, et al.
Published: (2023)
by: Wang, Fangye, et al.
Published: (2023)
Mitigate Position Bias with Coupled Ranking Bias on CTR Prediction
by: Zhao, Yao, et al.
Published: (2024)
by: Zhao, Yao, et al.
Published: (2024)
Polyhedral Conic Classifier for CTR Prediction
by: Turkmen, Beyza, et al.
Published: (2024)
by: Turkmen, Beyza, et al.
Published: (2024)
Unleashing the Potential of Sparse Attention on Long-term Behaviors for CTR Prediction
by: Lai, Weijiang, et al.
Published: (2026)
by: Lai, Weijiang, et al.
Published: (2026)
Feature Staleness Aware Incremental Learning for CTR Prediction
by: Wang, Zhikai, et al.
Published: (2025)
by: Wang, Zhikai, et al.
Published: (2025)
DUET: Dual Model Co-Training for Entire Space CTR Prediction
by: Xiao, Yutian, et al.
Published: (2025)
by: Xiao, Yutian, et al.
Published: (2025)
Enhancing CTR Prediction with De-correlated Expert Networks
by: Wang, Jiancheng, et al.
Published: (2025)
by: Wang, Jiancheng, et al.
Published: (2025)
RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction
by: Wu, Song-Li, et al.
Published: (2023)
by: Wu, Song-Li, et al.
Published: (2023)
Exploring Scaling Laws of CTR Model for Online Performance Improvement
by: Lai, Weijiang, et al.
Published: (2025)
by: Lai, Weijiang, et al.
Published: (2025)
LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction
by: Tang, Jiakai, et al.
Published: (2026)
by: Tang, Jiakai, et al.
Published: (2026)
FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction
by: Li, Honghao, et al.
Published: (2024)
by: Li, Honghao, et al.
Published: (2024)
DAIAN: Deep Adaptive Intent-Aware Network for CTR Prediction in Trigger-Induced Recommendation
by: Lv, Zhihao, et al.
Published: (2026)
by: Lv, Zhihao, et al.
Published: (2026)
FedMM: Federated Collaborative Signal Quantization for Multi-Market CTR Prediction
by: Zhang, Jun, et al.
Published: (2026)
by: Zhang, Jun, et al.
Published: (2026)
Star+: A New Multi-Domain Model for CTR Prediction
by: Yeşil, Çağrı, et al.
Published: (2024)
by: Yeşil, Çağrı, et al.
Published: (2024)
The Effects of Data Split Strategies on the Offline Experiments for CTR Prediction
by: Turksoy, Ramazan Tarik, et al.
Published: (2024)
by: Turksoy, Ramazan Tarik, et al.
Published: (2024)
STEC: See-Through Transformer-based Encoder for CTR Prediction
by: Dilbaz, Serdarcan, et al.
Published: (2023)
by: Dilbaz, Serdarcan, et al.
Published: (2023)
Modeling Long-term User Behaviors with Diffusion-driven Multi-interest Network for CTR Prediction
by: Lai, Weijiang, et al.
Published: (2025)
by: Lai, Weijiang, et al.
Published: (2025)
LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction
by: Song, Xin, et al.
Published: (2025)
by: Song, Xin, et al.
Published: (2025)
Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction
by: Li, Honghao, et al.
Published: (2025)
by: Li, Honghao, et al.
Published: (2025)
Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendation
by: Xiao, Zhibo, et al.
Published: (2024)
by: Xiao, Zhibo, et al.
Published: (2024)
RIA: A Ranking-Infused Approach for Optimized listwise CTR Prediction
by: Zhang, Guoxiao, et al.
Published: (2025)
by: Zhang, Guoxiao, et al.
Published: (2025)
From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction
by: Yan, Bencheng, et al.
Published: (2025)
by: Yan, Bencheng, et al.
Published: (2025)
CTR-Guided Generative Query Suggestion in Conversational Search
by: Min, Erxue, et al.
Published: (2025)
by: Min, Erxue, et al.
Published: (2025)
Field Matters: A Lightweight LLM-enhanced Method for CTR Prediction
by: Cui, Yu, et al.
Published: (2025)
by: Cui, Yu, et al.
Published: (2025)
Similar Items
-
Feature Interaction Fusion Self-Distillation Network For CTR Prediction
by: Sang, Lei, et al.
Published: (2024) -
CETN: Contrast-enhanced Through Network for CTR Prediction
by: Li, Honghao, et al.
Published: (2023) -
Enhancing CTR Prediction through Sequential Recommendation Pre-training: Introducing the SRP4CTR Framework
by: Han, Ruidong, et al.
Published: (2024) -
Explainable CTR Prediction via LLM Reasoning
by: Yu, Xiaohan, et al.
Published: (2024) -
MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths
by: Zhang, Moyu, et al.
Published: (2025)