Learning-To-Rank

Learning to rank is the application of machine learning to build ranking models. Some common use cases for ranking models are information retrieval (e.g., web search) and news feeds application (think Twitter, Facebook, Instagram).

Papers

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Showing 76–100 of 753 papers

Title	Date	Tasks	Status	Score
Learning to Rank Ace Neural Architectures via Normalized Discounted Cumulative Gain	Aug 6, 2021	Learning-To-RankNeural Architecture Search	CodeCode Available	5
A Probabilistic Position Bias Model for Short-Video Recommendation Feeds	Jul 26, 2023	Learning-To-RankPosition	CodeCode Available	5
Learning to Rank Patches for Unbiased Image Redundancy Reduction	Mar 31, 2024	Image ReconstructionInductive Bias	CodeCode Available	5
Distance-based Positive and Unlabeled Learning for Ranking	May 20, 2020	Learning-To-RankSpecificity	CodeCode Available	5
Learning to rank for censored survival data	Jun 6, 2018	Learning-To-RankSurvival Analysis	CodeCode Available	5
Learning to Rank Context for Named Entity Recognition Using a Synthetic Dataset	Oct 16, 2023	Language ModelingLanguage Modelling	CodeCode Available	5
Learning to Rank from Relevance Judgments Distributions	Feb 13, 2022	Learning-To-Rank	CodeCode Available	5
Unbiased Learning to Rank with Unbiased Propensity Estimation	Apr 16, 2018	Learning-To-Rankparameter estimation	CodeCode Available	5
An Offline Metric for the Debiasedness of Click Models	Apr 19, 2023	counterfactualLearning-To-Rank	CodeCode Available	5
Learning to Explain Entity Relationships in Knowledge Graphs	Jul 1, 2015	Knowledge GraphsLearning-To-Rank	CodeCode Available	5
Learning-To-Rank Approach for Identifying Everyday Objects Using a Physical-World Search Engine	Dec 26, 2023	Learning-To-Rank	CodeCode Available	5
Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision	May 6, 2025	Learning-To-RankSelf-Supervised Learning	CodeCode Available	5
LaSER: Language-Specific Event Recommendation	Feb 24, 2023	Information RetrievalLearning-To-Rank	CodeCode Available	5
Learning a Deep Listwise Context Model for Ranking Refinement	Apr 16, 2018	Information RetrievalLearning-To-Rank	CodeCode Available	5
Learning to Rank Aspects and Opinions for Comparative Explanations	Jan 16, 2025	Explainable RecommendationLearning-To-Rank	CodeCode Available	5
Learning to Rank Visual Stories From Human Ranking Data	May 1, 2022	Learning-To-RankText Generation	CodeCode Available	5
Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank?	May 13, 2024	feature selectionInterpretable Machine Learning	CodeCode Available	5
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study	Apr 4, 2024	counterfactualLearning-To-Rank	CodeCode Available	5
Is Non-IID Data a Threat in Federated Online Learning to Rank?	Apr 20, 2022	Federated LearningInformation Retrieval	CodeCode Available	5
Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVM	Feb 16, 2025	Learning-To-RankRetrieval	CodeCode Available	5
An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation	Dec 24, 2021	Combinatorial OptimizationDeep Reinforcement Learning	CodeCode Available	5
Intersection of Parallels as an Early Stopping Criterion	Aug 19, 2022	counterfactualLearning-To-Rank	CodeCode Available	5
Learning Cluster Representatives for Approximate Nearest Neighbor Search	Dec 8, 2024	ClusteringInformation Retrieval	CodeCode Available	5
Joint Optimization of Cascade Ranking Models	Feb 11, 2019	Ad-Hoc Information RetrievalDocument Ranking	CodeCode Available	5
ImitAL: Learned Active Learning Strategy on Synthetic Data	Aug 24, 2022	Active LearningInformativeness	CodeCode Available	5

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