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 681–690 of 753 papers

Title	Date	Tasks	Status
Learning to Rank from Relevance Judgments Distributions	Feb 13, 2022	Learning-To-Rank	CodeCode Available
On Curriculum Learning for Commonsense Reasoning	Jul 1, 2022	HellaSwagLearning-To-Rank	CodeCode Available
Ranking-Incentivized Quality Preserving Content Modification	May 26, 2020	Learning-To-RankRetrieval	CodeCode Available
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank	Sep 27, 2023	Learning-To-Rank	CodeCode Available
Automatic Quality Estimation for Natural Language Generation: Ranting (Jointly Rating and Ranking)	Oct 10, 2019	Learning-To-RankText Generation	CodeCode Available
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank	May 24, 2023	Learning-To-RankOut-of-Distribution Detection	CodeCode Available
Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document	Sep 14, 2021	AllFact Checking	CodeCode Available
A Recurrent Model for Collective Entity Linking with Adaptive Features	Apr 3, 2020	Deep LearningEntity Disambiguation	CodeCode Available
RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models	Mar 24, 2024	Information RetrievalLearning-To-Rank	CodeCode Available
Ranking Structured Objects with Graph Neural Networks	Apr 18, 2021	Graph RankingGraph Regression	CodeCode Available

Show:10 25 50

← PrevPage 69 of 76Next →

No leaderboard results yet.