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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

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Showing 76–100 of 753 papers

TitleStatusHype
Learning to Rank for Maps at Airbnb—0
Pistis-RAG: Enhancing Retrieval-Augmented Generation with Human Feedback—0
FIRST: Faster Improved Listwise Reranking with Single Token DecodingCode2
Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language ModelsCode2
Step-level Value Preference Optimization for Mathematical ReasoningCode3
Modeling User Retention through Generative Flow NetworksCode1
MrRank: Improving Question Answering Retrieval System through Multi-Result Ranking Model—0
Towards Explainable Test Case Prioritisation with Learning-to-Rank Models—0
GotFunding: A grant recommendation system based on scientific articles—0
Dual-Branch Network for Portrait Image Quality AssessmentCode1
Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank?Code0
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems—0
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank—0
Metalearners for Ranking Treatment Effects—0
Efficient and Responsible Adaptation of Large Language Models for Robust Top-k Recommendations—0
Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted TreesCode0
A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor SearchCode0
Learning to rank quantum circuits for hardware-optimized performance enhancement—0
Chiplet Placement Order Exploration Based on Learning to Rank with Graph Representation—0
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility StudyCode0
Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search DatasetCode0
Towards an In-Depth Comprehension of Case Relevance for Better Legal Retrieval—0
Learning to Rank Patches for Unbiased Image Redundancy ReductionCode0
RankingSHAP -- Listwise Feature Attribution Explanations for Ranking ModelsCode0
Metasql: A Generate-then-Rank Framework for Natural Language to SQL TranslationCode1
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