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 176–200 of 753 papers

Title	Date	Tasks	Status	Hype
Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization	Apr 26, 2023	counterfactualLearning-To-Rank	CodeCode Available	0
THUIR at WSDM Cup 2023 Task 1: Unbiased Learning to Rank	Apr 25, 2023	Learning-To-Rank	CodeCode Available	1
Can Perturbations Help Reduce Investment Risks? Risk-Aware Stock Recommendation via Split Variational Adversarial Training	Apr 20, 2023	Learning-To-Rank	—Unverified	0
An Offline Metric for the Debiasedness of Click Models	Apr 19, 2023	counterfactualLearning-To-Rank	CodeCode Available	0
Revisiting the Role of Similarity and Dissimilarity in Best Counter Argument Retrieval	Apr 18, 2023	Argument RetrievalLearning-To-Rank	—Unverified	0
Learning To Rank Resources with GNN	Apr 17, 2023	Graph Neural NetworkInformation Retrieval	—Unverified	0
Metric-agnostic Ranking Optimization	Apr 17, 2023	Information RetrievalLearning-To-Rank	—Unverified	0
OPI at SemEval 2023 Task 1: Image-Text Embeddings and Multimodal Information Retrieval for Visual Word Sense Disambiguation	Apr 14, 2023	Information RetrievalLearning-To-Rank	—Unverified	0
Explicit and Implicit Semantic Ranking Framework	Apr 11, 2023	Learning-To-RankText Summarization	—Unverified	0
Sentence-Level Relation Extraction via Contrastive Learning with Descriptive Relation Prompts	Apr 11, 2023	Contrastive LearningDescriptive	—Unverified	0
Deep Ranking Ensembles for Hyperparameter Optimization	Mar 27, 2023	Hyperparameter OptimizationLearning-To-Rank	—Unverified	0
Unbiased Learning to Rank with Biased Continuous Feedback	Mar 8, 2023	Learning-To-RankPosition	—Unverified	0
Tile Networks: Learning Optimal Geometric Layout for Whole-page Recommendation	Mar 3, 2023	Learning-To-Rankreinforcement-learning	—Unverified	0
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	0
Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank	Feb 28, 2023	Learning-To-Rank	—Unverified	0
LaSER: Language-Specific Event Recommendation	Feb 24, 2023	Information RetrievalLearning-To-Rank	CodeCode Available	0
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	0
Ensemble Ranking Model with Multiple Pretraining Strategies for Web Search	Feb 18, 2023	Learning-To-Rank	—Unverified	0
Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank	Feb 15, 2023	Learning-To-Rank	—Unverified	0
Lero: A Learning-to-Rank Query Optimizer	Feb 14, 2023	Binary ClassificationLearning-To-Rank	CodeCode Available	1
PASSerRank: Prediction of Allosteric Sites with Learning to Rank	Feb 2, 2023	Drug DiscoveryLearning-To-Rank	CodeCode Available	0
Learning to Rank Normalized Entropy Curves with Differentiable Window Transformation	Jan 25, 2023	Learning-To-RankRecommendation Systems	—Unverified	0
Overcoming Prior Misspecification in Online Learning to Rank	Jan 25, 2023	Learning-To-Rank	CodeCode Available	0
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval	Jan 11, 2023	Conversational SearchInformation Retrieval	CodeCode Available	0
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank	Dec 28, 2022	Learning-To-Rank	—Unverified	0

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