Click-Through Rate Prediction

133 papers with code • 19 benchmarks • 6 datasets

Click-through rate prediction is the task of predicting the likelihood that something on a website (such as an advertisement) will be clicked.

( Image credit: Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction )

Libraries

Use these libraries to find Click-Through Rate Prediction models and implementations
30 papers
293
27 papers
749
25 papers
7,303
7 papers
749
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Understanding the Ranking Loss for Recommendation with Sparse User Feedback

skylerlinn/understanding-the-ranking-loss 21 Mar 2024

In this paper, we uncover a new challenge associated with BCE loss in scenarios with sparse positive feedback, such as CTR prediction: the gradient vanishing for negative samples.

3
21 Mar 2024

Discrete Semantic Tokenization for Deep CTR Prediction

jyonn/semantictokenizer 13 Mar 2024

Incorporating item content information into click-through rate (CTR) prediction models remains a challenge, especially with the time and space constraints of industrial scenarios.

5
13 Mar 2024

Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization

nus-hpc-ai-lab/helen 23 Feb 2024

We explore the typical data characteristics and optimization statistics of CTR prediction, revealing a strong positive correlation between the top hessian eigenvalue and feature frequency.

9
23 Feb 2024

Understanding and Counteracting Feature-Level Bias in Click-Through Rate Prediction

mitao-cat/feature-level_bias 6 Feb 2024

We conduct a theoretical analysis of the learning process for the weights in the linear component, revealing how group-wise properties of training data influence them.

2
06 Feb 2024

A Unified Framework for Multi-Domain CTR Prediction via Large Language Models

archersama/uni-ctr 17 Dec 2023

Click-Through Rate (CTR) prediction is a crucial task in online recommendation platforms as it involves estimating the probability of user engagement with advertisements or items by clicking on them.

3
17 Dec 2023

CETN: Contrast-enhanced Through Network for CTR Prediction

salmon1802/cetn 15 Dec 2023

Click-through rate (CTR) Prediction is a crucial task in personalized information retrievals, such as industrial recommender systems, online advertising, and web search.

5
15 Dec 2023

UFIN: Universal Feature Interaction Network for Multi-Domain Click-Through Rate Prediction

rucaibox/ufin 27 Nov 2023

To address the above issue, we propose the Universal Feature Interaction Network (UFIN) approach for CTR prediction.

8
27 Nov 2023

A Comprehensive Summarization and Evaluation of Feature Refinement Modules for CTR Prediction

codectr/refinectr 8 Nov 2023

In addition, we present a new architecture of assigning independent FR modules to separate sub-networks for parallel CTR models, as opposed to the conventional method of inserting a shared FR module on top of the embedding layer.

7
08 Nov 2023

RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction

yansuoyuli/reform 26 Sep 2023

Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user.

0
26 Sep 2023