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 651–675 of 753 papers

Title	Date	Tasks	Status
Autoregressive Reasoning over Chains of Facts with Transformers	Dec 17, 2020	Learning-To-Rank	CodeCode Available
SARDINE: A Simulator for Automated Recommendation in Dynamic and Interactive Environments	Nov 28, 2023	counterfactualLearning-To-Rank	CodeCode Available
Uncoupled Regression from Pairwise Comparison Data	May 31, 2019	Learning-To-Rankregression	CodeCode Available
Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank	Oct 7, 2020	Learning-To-RankSentence	CodeCode Available
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation	Oct 29, 2023	Federated LearningInformation Retrieval	CodeCode Available
RAMQA: A Unified Framework for Retrieval-Augmented Multi-Modal Question Answering	Jan 23, 2025	DecoderInformation Retrieval	CodeCode Available
Using clarification questions to improve software developers’ Web search	Jul 1, 2022	Learning-To-Rankvalid	CodeCode Available
Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank	Jun 3, 2022	Learning-To-Rank	CodeCode Available
Learning-To-Rank Approach for Identifying Everyday Objects Using a Physical-World Search Engine	Dec 26, 2023	Learning-To-Rank	CodeCode Available
Learning to Rank Aspects and Opinions for Comparative Explanations	Jan 16, 2025	Explainable RecommendationLearning-To-Rank	CodeCode Available
ImitAL: Learned Active Learning Strategy on Synthetic Data	Aug 24, 2022	Active LearningInformativeness	CodeCode Available
Deep Metric Learning to Rank	Jun 1, 2019	Image RetrievalLearning-To-Rank	CodeCode Available
Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees	Apr 18, 2024	FairnessLearning-To-Rank	CodeCode Available
DCM Bandits: Learning to Rank with Multiple Clicks	Feb 9, 2016	Learning-To-Rank	CodeCode Available
An Offline Metric for the Debiasedness of Click Models	Apr 19, 2023	counterfactualLearning-To-Rank	CodeCode Available
New Insights into Metric Optimization for Ranking-based Recommendation	Jun 4, 2021	Learning-To-RankRecommendation Systems	CodeCode Available
Counterfactual Learning to Rank using Heterogeneous Treatment Effect Estimation	Jul 19, 2020	counterfactualHeterogeneous Treatment Effect Estimation	CodeCode Available
Learning to Rank Context for Named Entity Recognition Using a Synthetic Dataset	Oct 16, 2023	Language ModelingLanguage Modelling	CodeCode Available
Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents	Nov 1, 2019	Learning-To-RankMulti-Hop Reading Comprehension	CodeCode Available
Mend The Learning Approach, Not the Data: Insights for Ranking E-Commerce Products	Jul 24, 2019	counterfactualLearning-To-Rank	CodeCode Available
Entity Linking within a Social Media Platform: A Case Study on Yelp	Oct 1, 2018	Entity LinkingLearning-To-Rank	CodeCode Available
Using clarification questions to improve software developers' Web search	Jul 26, 2022	Learning-To-Rankvalid	CodeCode Available
Learning to rank for censored survival data	Jun 6, 2018	Learning-To-RankSurvival Analysis	CodeCode Available
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval	Jan 11, 2023	Conversational SearchInformation Retrieval	CodeCode Available
Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System	Sep 19, 2018	Knowledge DistillationLearning-To-Rank	CodeCode Available

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