SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–525 of 753 papers

TitleStatusHype
On the Calibration and Uncertainty of Neural Learning to Rank Models for Conversational Search—0
On the Consistency of AUC Pairwise Optimization—0
On the ERM Principle with Networked Data—0
Activity Auto-Completion: Predicting Human Activities From Partial Videos—0
On The Structure of Parametric Tournaments with Application to Ranking from Pairwise Comparisons—0
Ontology-Based Retrieval \& Neural Approaches for BioASQ Ideal Answer Generation—0
OPI at SemEval 2023 Task 1: Image-Text Embeddings and Multimodal Information Retrieval for Visual Word Sense Disambiguation—0
Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation—0
Weakly-supervised Contextualization of Knowledge Graph Facts—0
Optimize What You Evaluate With: A Simple Yet Effective Framework For Direct Optimization Of IR Metrics—0
Unbiased Learning to Rank: Counterfactual and Online Approaches—0
Optimizing Preference Alignment with Differentiable NDCG Ranking—0
Optimizing Ranking Models in an Online Setting—0
Optimizing Ranking Systems Online as Bandits—0
Neural IR Meets Graph Embedding: A Ranking Model for Product Search—0
Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claims—0
Unbiased Learning to Rank: Online or Offline?—0
Pairwise Judgment Formulation for Semantic Embedding Model in Web Search—0
A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization—0
Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction—0
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions—0
Par4Sim -- Adaptive Paraphrasing for Text Simplification—0
Pareto Pairwise Ranking for Fairness Enhancement of Recommender Systems—0
Unbiased Learning-to-Rank with Biased Feedback—0
Unbiased Learning to Rank with Biased Continuous Feedback—0
Show:102550
← PrevPage 21 of 31Next →

No leaderboard results yet.