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 626–650 of 753 papers

Title	Date	Tasks	Status
Sustainable transparency in Recommender Systems: Bayesian Ranking of Images for Explainability	Jul 27, 2023	Explainable RecommendationExplanation Generation	CodeCode Available
Robust Generalization and Safe Query-Specialization in Counterfactual Learning to Rank	Feb 11, 2021	counterfactualLearning-To-Rank	CodeCode Available
A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search	Apr 17, 2024	ClusteringInformation Retrieval	CodeCode Available
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank	Feb 17, 2019	Active LearningCrowd Counting	CodeCode Available
When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank	Aug 24, 2020	counterfactualLearning-To-Rank	CodeCode Available
Intersection of Parallels as an Early Stopping Criterion	Aug 19, 2022	counterfactualLearning-To-Rank	CodeCode Available
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs	Feb 19, 2024	Document RankingLearning-To-Rank	CodeCode Available
Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVM	Feb 16, 2025	Learning-To-RankRetrieval	CodeCode Available
Probabilistic Permutation Graph Search: Black-Box Optimization for Fairness in Ranking	Apr 28, 2022	FairnessLearning-To-Rank	CodeCode Available
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits	Aug 8, 2024	Exposure FairnessFairness	CodeCode Available
Mixture-Based Correction for Position and Trust Bias in Counterfactual Learning to Rank	Aug 19, 2021	counterfactualLearning-To-Rank	CodeCode Available
Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint	Jul 24, 2020	ClusteringFeature Importance	CodeCode Available
Model-based Unbiased Learning to Rank	Jul 24, 2022	Information RetrievalLearning-To-Rank	CodeCode Available
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank	Nov 30, 2018	Document SummarizationLearning-To-Rank	CodeCode Available
Modeling Label Ambiguity for Neural List-Wise Learning to Rank	Jul 24, 2017	Learning-To-Rank	CodeCode Available
PRUNE: Preserving Proximity and Global Ranking for Network Embedding	Dec 1, 2017	Community DetectionGeneral Classification	CodeCode Available
Exact Passive-Aggressive Algorithms for Learning to Rank Using Interval Labels	Aug 18, 2018	Learning-To-Rank	CodeCode Available
Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization	Apr 26, 2023	counterfactualLearning-To-Rank	CodeCode Available
Differentiable Unbiased Online Learning to Rank	Sep 22, 2018	Learning-To-Rank	CodeCode Available
Improving Pairwise Ranking for Multi-label Image Classification	Apr 11, 2017	ClassificationGeneral Classification	CodeCode Available
Safe Exploration for Optimizing Contextual Bandits	Feb 2, 2020	counterfactualInformation Retrieval	CodeCode Available
More Accurate Question Answering on Freebase	Oct 1, 2015	Learning-To-RankQuestion Answering	CodeCode Available
Learning to Explain Entity Relationships in Knowledge Graphs	Jul 1, 2015	Knowledge GraphsLearning-To-Rank	CodeCode Available
ImitAL: Learning Active Learning Strategies from Synthetic Data	Aug 17, 2021	Active LearningImitation Learning	CodeCode Available
Quantitative Analysis of Automatic Image Cropping Algorithms: A Dataset and Comparative Study	Jan 5, 2017	Image CroppingLearning-To-Rank	CodeCode Available

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