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 191–200 of 753 papers

Title	Date	Tasks	Status	Score
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval	Jan 11, 2023	Conversational SearchInformation Retrieval	CodeCode Available	5
Fitting Sentence Level Translation Evaluation with Many Dense Features	Oct 1, 2014	Learning-To-RankMachine Translation	CodeCode Available	5
FAIRY: A Framework for Understanding Relationships between Users' Actions and their Social Feeds	Aug 8, 2019	Learning-To-Rank	CodeCode Available	5
Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document	Sep 14, 2021	AllFact Checking	CodeCode Available	5
Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems	Feb 20, 2023	Learning-To-RankReinforcement Learning (RL)	CodeCode Available	5
Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees	Apr 18, 2024	FairnessLearning-To-Rank	CodeCode Available	5
Contextual Semibandits via Supervised Learning Oracles	Feb 20, 2015	Decision MakingLearning-To-Rank	CodeCode Available	5
Exact Passive-Aggressive Algorithms for Learning to Rank Using Interval Labels	Aug 18, 2018	Learning-To-Rank	CodeCode Available	5
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank	Feb 17, 2019	Active LearningCrowd Counting	CodeCode Available	5
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs	Feb 19, 2024	Document RankingLearning-To-Rank	CodeCode Available	5

Show:10 25 50

← PrevPage 20 of 76Next →

No leaderboard results yet.