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 551–560 of 753 papers

Title	Date	Tasks	Status
Uncertain Natural Language Inference	Sep 6, 2019	Learning-To-RankNatural Language Inference	—Unverified
PTDE: Personalized Training with Distilled Execution for Multi-Agent Reinforcement Learning	Oct 17, 2022	Learning-To-RankMulti-agent Reinforcement Learning	—Unverified
Alternative Objective Functions for Training MT Evaluation Metrics	Jul 1, 2017	Learning-To-RankMachine Translation	—Unverified
Quad-networks: unsupervised learning to rank for interest point detection	Nov 22, 2016	Interest Point DetectionLearning-To-Rank	—Unverified
Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity	Dec 1, 2011	Active LearningLearning-To-Rank	—Unverified
Query-level Early Exit for Additive Learning-to-Rank Ensembles	Apr 30, 2020	Learning-To-Rank	—Unverified
Query Understanding via Entity Attribute Identification	Sep 23, 2018	AttributeLearning-To-Rank	—Unverified
QU-IR at SemEval 2016 Task 3: Learning to Rank on Arabic Community Question Answering Forums with Word Embedding	Jun 1, 2016	Community Question AnsweringLearning-To-Rank	—Unverified
A Line in the Sand: Recommendation or Ad-hoc Retrieval?	Jul 21, 2018	Collaborative FilteringLearning-To-Rank	—Unverified
Unconfounded Propensity Estimation for Unbiased Ranking	May 17, 2023	Learning-To-Rank	—Unverified

Show:10 25 50

← PrevPage 56 of 76Next →

No leaderboard results yet.