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 201–225 of 753 papers

Title	Date	Tasks	Status	Score
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs	Feb 19, 2024	Document RankingLearning-To-Rank	CodeCode Available	5
On the Problem of Underranking in Group-Fair Ranking	Sep 24, 2020	FairnessLearning-To-Rank	CodeCode Available	5
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank	Feb 17, 2019	Active LearningCrowd Counting	CodeCode Available	5
RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models	Mar 24, 2024	Information RetrievalLearning-To-Rank	CodeCode Available	5
Rank Pooling for Action Recognition	Dec 6, 2015	Action RecognitionGesture Recognition	CodeCode Available	5
Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application	Mar 2, 2018	Decision MakingLearning-To-Rank	CodeCode Available	5
Groupwise Query Performance Prediction with BERT	Apr 25, 2022	Learning-To-RankPrediction	CodeCode Available	5
Safe Exploration for Optimizing Contextual Bandits	Feb 2, 2020	counterfactualInformation Retrieval	CodeCode Available	5
Hidden or Inferred: Fair Learning-To-Rank with Unknown Demographics	Jul 24, 2024	AttributeFairness	CodeCode Available	5
Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents	Nov 1, 2019	Learning-To-RankMulti-Hop Reading Comprehension	CodeCode Available	5
Contextual Semibandits via Supervised Learning Oracles	Feb 20, 2015	Decision MakingLearning-To-Rank	CodeCode Available	5
Fitting Sentence Level Translation Evaluation with Many Dense Features	Oct 1, 2014	Learning-To-RankMachine Translation	CodeCode Available	5
Distance-based Positive and Unlabeled Learning for Ranking	May 20, 2020	Learning-To-RankSpecificity	CodeCode Available	5
ShaRP: A Novel Feature Importance Framework for Ranking	Jan 30, 2024	Feature ImportanceLearning-To-Rank	CodeCode Available	5
Content Selection for Real-time Sports News Construction from Commentary Texts	Sep 1, 2017	Document SummarizationFeature Engineering	—Unverified	0
Content-Based Features to Rank Influential Hidden Services of the Tor Darknet	Oct 5, 2019	Learning-To-RankNER	—Unverified	0
A scale invariant ranking function for learning-to-rank: a real-world use case	Oct 21, 2021	Learning-To-RankRecommendation Systems	—Unverified	0
Constrained Multi-Task Learning for Automated Essay Scoring	Aug 1, 2016	Automated Essay ScoringLearning-To-Rank	—Unverified	0
Consistent Position Bias Estimation without Online Interventions for Learning-to-Rank	Jun 9, 2018	counterfactualLearning-To-Rank	—Unverified	0
ARSM Gradient Estimator for Supervised Learning to Rank	Nov 1, 2019	Learning-To-Rank	—Unverified	0
A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization	Dec 4, 2023	Learning-To-RankStochastic Optimization	—Unverified	0
Computational and Statistical Tradeoffs in Learning to Rank	Aug 22, 2016	Learning-To-Rank	—Unverified	0
Compound virtual screening by learning-to-rank with gradient boosting decision tree and enrichment-based cumulative gain	May 4, 2022	Information RetrievalLearning-To-Rank	—Unverified	0
A Representation Theory for Ranking Functions	Dec 1, 2014	Learning-To-RankReranking	—Unverified	0
Community-based Cyberreading for Information Understanding	Mar 27, 2021	Learning-To-Rank	—Unverified	0

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