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 226–250 of 753 papers

Title	Date	Tasks	Status
Sentence-Level Relation Extraction via Contrastive Learning with Descriptive Relation Prompts	Apr 11, 2023	Contrastive LearningDescriptive	—Unverified
Explicit and Implicit Semantic Ranking Framework	Apr 11, 2023	Learning-To-RankText Summarization	—Unverified
Deep Ranking Ensembles for Hyperparameter Optimization	Mar 27, 2023	Hyperparameter OptimizationLearning-To-Rank	—Unverified
Unbiased Learning to Rank with Biased Continuous Feedback	Mar 8, 2023	Learning-To-RankPosition	—Unverified
Tile Networks: Learning Optimal Geometric Layout for Whole-page Recommendation	Mar 3, 2023	Learning-To-Rankreinforcement-learning	—Unverified
Fine-grained Emotional Control of Text-To-Speech: Learning To Rank Inter- And Intra-Class Emotion Intensities	Mar 2, 2023	Learning-To-Ranktext-to-speech	—Unverified
Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank	Feb 28, 2023	Learning-To-Rank	—Unverified
LaSER: Language-Specific Event Recommendation	Feb 24, 2023	Information RetrievalLearning-To-Rank	CodeCode Available
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems	Feb 20, 2023	Learning-To-RankReinforcement Learning (RL)	CodeCode Available
Ensemble Ranking Model with Multiple Pretraining Strategies for Web Search	Feb 18, 2023	Learning-To-Rank	—Unverified
Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank	Feb 15, 2023	Learning-To-Rank	—Unverified
PASSerRank: Prediction of Allosteric Sites with Learning to Rank	Feb 2, 2023	Drug DiscoveryLearning-To-Rank	CodeCode Available
Overcoming Prior Misspecification in Online Learning to Rank	Jan 25, 2023	Learning-To-Rank	CodeCode Available
Learning to Rank Normalized Entropy Curves with Differentiable Window Transformation	Jan 25, 2023	Learning-To-RankRecommendation Systems	—Unverified
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval	Jan 11, 2023	Conversational SearchInformation Retrieval	CodeCode Available
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank	Dec 28, 2022	Learning-To-Rank	—Unverified
Rank-LIME: Local Model-Agnostic Feature Attribution for Learning to Rank	Dec 24, 2022	Decision MakingInformation Retrieval	—Unverified
Coarse-to-Fine Contrastive Learning on Graphs	Dec 13, 2022	Contrastive LearningLearning-To-Rank	—Unverified
Multi-Task Off-Policy Learning from Bandit Feedback	Dec 9, 2022	Learning-To-RankRecommendation Systems	—Unverified
Pareto Pairwise Ranking for Fairness Enhancement of Recommender Systems	Dec 6, 2022	FairnessLearning-To-Rank	—Unverified
Learning to Rank Graph-based Application Objects on Heterogeneous Memories	Nov 4, 2022	Learning-To-Rank	—Unverified
Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance	Nov 2, 2022	Learning-To-Rankregression	—Unverified
Whole Page Unbiased Learning to Rank	Oct 19, 2022	Causal DiscoveryInformation Retrieval	—Unverified
PTDE: Personalized Training with Distilled Execution for Multi-Agent Reinforcement Learning	Oct 17, 2022	Learning-To-RankMulti-agent Reinforcement Learning	—Unverified
Off-policy evaluation for learning-to-rank via interpolating the item-position model and the position-based model	Oct 15, 2022	Learning-To-Rankmodel	—Unverified

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