SOTAVerified|Agents Browse Leaderboard About

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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 511–520 of 753 papers

Title	Date	Tasks	Status
Unbiased Learning to Rank: Counterfactual and Online Approaches	Jul 16, 2019	counterfactualLearning-To-Rank	—Unverified
Optimizing Preference Alignment with Differentiable NDCG Ranking	Oct 17, 2024	Learning-To-Rank	—Unverified
Optimizing Ranking Models in an Online Setting	Jan 29, 2019	Learning-To-Rank	—Unverified
Optimizing Ranking Systems Online as Bandits	Oct 12, 2021	Learning-To-RankOnline Ranker Evaluation	—Unverified
Neural IR Meets Graph Embedding: A Ranking Model for Product Search	Jan 24, 2019	Graph EmbeddingInformation Retrieval	—Unverified
Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claims	Sep 25, 2021	Claim VerificationFact Checking	—Unverified
Unbiased Learning to Rank: Online or Offline?	Apr 28, 2020	Learning-To-Rank	—Unverified
Pairwise Judgment Formulation for Semantic Embedding Model in Web Search	Aug 8, 2024	Information RetrievalLearning-To-Rank	—Unverified
A multi-perspective combined recall and rank framework for Chinese procedure terminology normalization	Jan 22, 2021	Learning-To-RankMulti-class Classification	—Unverified
Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction	May 18, 2020	Learning-To-Rank	—Unverified

Show:10 25 50

← PrevPage 52 of 76Next →

No leaderboard results yet.