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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 41–50 of 753 papers

TitleStatusHype
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal ClassificationCode1
Learning to Rank Microphones for Distant Speech RecognitionCode1
Controlling Fairness and Bias in Dynamic Learning-to-RankCode1
Introducing LETOR 4.0 DatasetsCode1
LiPO: Listwise Preference Optimization through Learning-to-RankCode1
Listwise Learning to Rank by Exploring Unique RatingsCode1
Accelerated Convergence for Counterfactual Learning to RankCode1
Dual-Branch Network for Portrait Image Quality AssessmentCode1
Hierarchical Entity Typing via Multi-level Learning to RankCode1
On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved PerformanceCode1
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