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 411–420 of 753 papers

Title	Date	Tasks	Status
Unconfounded Propensity Estimation for Unbiased Ranking	May 17, 2023	Learning-To-Rank	—Unverified
Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality	Jul 29, 2021	Learning-To-RankRecommendation Systems	—Unverified
Understanding the Effects of the Baidu-ULTR Logging Policy on Two-Tower Models	Sep 18, 2024	Learning-To-Rank	—Unverified
Understanding the Gist of Images - Ranking of Concepts for Multimedia Indexing	Sep 23, 2018	Learning-To-Rank	—Unverified
Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank	Jul 4, 2023	Information RetrievalLearning-To-Rank	—Unverified
Universalizing Weak Supervision	Dec 7, 2021	Computational EfficiencyLearning-To-Rank	—Unverified
Universal Text Representation from BERT: An Empirical Study	Oct 17, 2019	Learning-To-RankNatural Language Inference	—Unverified
U-rank: Utility-oriented Learning to Rank with Implicit Feedback	Nov 1, 2020	Click-Through Rate PredictionLearning-To-Rank	—Unverified
Using Learning-To-Rank to Enhance NLM Medical Text Indexer Results	Aug 1, 2016	Learning-To-Rank	—Unverified
Valid Explanations for Learning to Rank Models	Apr 29, 2020	Learning-To-Rankvalid	—Unverified

Show:10 25 50

← PrevPage 42 of 76Next →

No leaderboard results yet.