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 676–700 of 753 papers

Title	Date	Tasks	Status
Contextual Semibandits via Supervised Learning Oracles	Feb 20, 2015	Decision MakingLearning-To-Rank	CodeCode Available
End-to-End Neural Ad-hoc Ranking with Kernel Pooling	Jun 20, 2017	Ad-Hoc Information RetrievalDocument Ranking	CodeCode Available
On the Problem of Underranking in Group-Fair Ranking	Sep 24, 2020	FairnessLearning-To-Rank	CodeCode Available
Off-policy evaluation for slate recommendation	May 16, 2016	Learning-To-RankOff-policy evaluation	CodeCode Available
Ranking for Relevance and Display Preferences in Complex Presentation Layouts	May 7, 2018	Deep Reinforcement LearningLearning-To-Rank	CodeCode Available
Learning to Rank from Relevance Judgments Distributions	Feb 13, 2022	Learning-To-Rank	CodeCode Available
On Curriculum Learning for Commonsense Reasoning	Jul 1, 2022	HellaSwagLearning-To-Rank	CodeCode Available
Ranking-Incentivized Quality Preserving Content Modification	May 26, 2020	Learning-To-RankRetrieval	CodeCode Available
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank	Sep 27, 2023	Learning-To-Rank	CodeCode Available
Automatic Quality Estimation for Natural Language Generation: Ranting (Jointly Rating and Ranking)	Oct 10, 2019	Learning-To-RankText Generation	CodeCode Available
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank	May 24, 2023	Learning-To-RankOut-of-Distribution Detection	CodeCode Available
Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document	Sep 14, 2021	AllFact Checking	CodeCode Available
A Recurrent Model for Collective Entity Linking with Adaptive Features	Apr 3, 2020	Deep LearningEntity Disambiguation	CodeCode Available
RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models	Mar 24, 2024	Information RetrievalLearning-To-Rank	CodeCode Available
Ranking Structured Objects with Graph Neural Networks	Apr 18, 2021	Graph RankingGraph Regression	CodeCode Available
How to Forget Clients in Federated Online Learning to Rank?	Jan 24, 2024	Learning-To-Rank	CodeCode Available
Hidden or Inferred: Fair Learning-To-Rank with Unknown Demographics	Jul 24, 2024	AttributeFairness	CodeCode Available
An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation	Dec 24, 2021	Combinatorial OptimizationDeep Reinforcement Learning	CodeCode Available
Duet at TREC 2019 Deep Learning Track	Dec 10, 2019	Deep LearningLearning-To-Rank	CodeCode Available
Calibration-Disentangled Learning and Relevance-Prioritized Reranking for Calibrated Sequential Recommendation	Aug 4, 2024	Learning-To-RankReranking	CodeCode Available
Learning to Rank Patches for Unbiased Image Redundancy Reduction	Mar 31, 2024	Image ReconstructionInductive Bias	CodeCode Available
To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions	Jul 15, 2019	Benchmarkingcounterfactual	CodeCode Available
Using Titles vs. Full-text as Source for Automated Semantic Document Annotation	May 15, 2017	ArticlesClassification	CodeCode Available
On the Impact of Outlier Bias on User Clicks	May 1, 2023	counterfactualLearning-To-Rank	CodeCode Available
Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank	Aug 20, 2020	Information RetrievalLearning-To-Rank	CodeCode Available

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