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Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation
Arxiv
0+阅读 · 10月29日
DUET: Dual Model Co-Training for Entire Space CTR Prediction
Arxiv
0+阅读 · 10月28日
Cross-Lingual Sponsored Search via Dual-Encoder and Graph Neural Networks for Context-Aware Query Translation in Advertising Platforms
Arxiv
0+阅读 · 10月27日
HoMer: Addressing Heterogeneities by Modeling Sequential and Set-wise Contexts for CTR Prediction
Arxiv
0+阅读 · 10月23日
Hierarchical LoRA MoE for Efficient CTR Model Scaling
Arxiv
0+阅读 · 10月12日
HoMer: Addressing Heterogeneities by Modeling Sequential and Set-wise Contexts for CTR Prediction
Arxiv
0+阅读 · 10月13日
MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths
Arxiv
0+阅读 · 10月10日
Robust autobidding for noisy conversion prediction models
Arxiv
0+阅读 · 10月9日
MetaSynth: Multi-Agent Metadata Generation from Implicit Feedback in Black-Box Systems
Arxiv
0+阅读 · 10月1日
Clicks Versus Conversion: Choosing a Recommender's Training Objective in E-Commerce
Arxiv
0+阅读 · 8月14日
Exploring Scaling Laws of CTR Model for Online Performance Improvement
Arxiv
0+阅读 · 8月21日
Exploring Scaling Laws of CTR Model for Online Performance Improvement
Arxiv
0+阅读 · 9月19日
CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction
Arxiv
0+阅读 · 8月5日
Revealing Covert Attention by Analyzing Human and Reinforcement Learning Agent Gameplay
Arxiv
0+阅读 · 4月15日
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation
Arxiv
0+阅读 · 3月21日
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