Cover Image

Learning to Rank with Variable Result Presentation Lengths

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Knyazev, Norman, Oosterhuis, Harrie
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)

Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees
by: Kang, Jingwei, et al.
Published: (2024)

Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)

Optimal Baseline Corrections for Off-Policy Contextual Bandits
by: Gupta, Shashank, et al.
Published: (2024)

Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I
by: Oosterhuis, Harrie, et al.
Published: (2024)

Optimizing Compound Retrieval Systems
by: Oosterhuis, Harrie, et al.
Published: (2025)

A Non-Parametric Choice Model That Learns How Users Choose Between Recommended Options
by: Krause, Thorsten, et al.
Published: (2025)

Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank?
by: Lyu, Lijun, et al.
Published: (2024)

A First Look at Selection Bias in Preference Elicitation for Recommendation
by: Gupta, Shashank, et al.
Published: (2024)

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing
by: Yan, Le, et al.
Published: (2024)

Following the Eye-Tracking Evidence: Established Web-Search Assumptions Fail in Carousel Interfaces
by: Kang, Jingwei, et al.
Published: (2026)

Harnessing Pairwise Ranking Prompting Through Sample-Efficient Ranking Distillation
by: Wu, Junru, et al.
Published: (2025)

Variable-Length Semantic IDs for Recommender Systems
by: Khrylchenko, Kirill
Published: (2026)

RewardRank: Optimizing True Learning-to-Rank Utility
by: Bhatt, Gaurav, et al.
Published: (2025)

Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation
by: Gomez, Camilo, et al.
Published: (2026)

Rethinking Click Models in Light of Carousel Interfaces: Theory-Based Categorization and Design of Click Models
by: Kang, Jingwei, et al.
Published: (2025)

RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
by: Chowdhury, Tanya, et al.
Published: (2024)

Learning Cascade Ranking as One Network
by: Wang, Yunli, et al.
Published: (2025)

Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems
by: Huang, Jin, et al.
Published: (2024)

Efficient Pointwise-Pairwise Learning-to-Rank for News Recommendation
by: Kannen, Nithish, et al.
Published: (2024)

Unlearning for Federated Online Learning to Rank: A Reproducibility Study
by: Tao, Yiling, et al.
Published: (2025)

A Design Space for Explainable Ranking and Ranking Models
by: Hazwani, I. Al, et al.
Published: (2022)

Adaptive Orchestration of Modular Generative Information Access Systems
by: Hoveyda, Mohanna, et al.
Published: (2025)

Correcting for Position Bias in Learning to Rank: A Control Function Approach
by: Islam, Md Aminul, et al.
Published: (2025)

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank
by: Hager, Philipp, et al.
Published: (2025)

RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation
by: Wu, Renzhi, et al.
Published: (2025)

Efficient and Effective Query Context-Aware Learning-to-Rank Model for Sequential Recommendation
by: Dzhoha, Andrii, et al.
Published: (2025)

DeepMTL2R: A Library for Deep Multi-task Learning to Rank
by: Dong, Chaosheng, et al.
Published: (2026)

CaliCausalRank: Calibrated Multi-Objective Ad Ranking with Robust Counterfactual Utility Optimization
by: Yang, Xikai, et al.
Published: (2026)

Enhancing Travel Decision-Making: A Contrastive Learning Approach for Personalized Review Rankings in Accommodations
by: Igebaria, Reda, et al.
Published: (2024)

Scalable In-context Ranking with Generative Models
by: Gupta, Nilesh, et al.
Published: (2025)

Linear-PAL: A Lightweight Ranker for Mitigating Shortcut Learning in Personalized, High-Bias Tabular Ranking
by: Pawar, Vipul Dinesh
Published: (2025)

Do Not Wait: Learning Re-Ranking Model Without User Feedback At Serving Time in E-Commerce
by: Wang, Yuan, et al.
Published: (2024)

EVNextTrade: Learning-to-Rank-Based Recommendation of Next Charging Nodes for EV-EV Energy Trading
by: Rahmana, Md Mahfujur, et al.
Published: (2026)

Blending Learning to Rank and Dense Representations for Efficient and Effective Cascades
by: Nardini, Franco Maria, et al.
Published: (2025)

MLPlatt: Simple Calibration Framework for Ranking Models
by: Bajger, Piotr, et al.
Published: (2026)

A Self-boosted Framework for Calibrated Ranking
by: Zhang, Shunyu, et al.
Published: (2024)

Multimodal Data Curation Through Ranked Retrieval
by: Muthukumar, Pratyush, et al.
Published: (2026)

Residual Multi-Task Learner for Applied Ranking
by: Fu, Cong, et al.
Published: (2024)

GenSERP: Large Language Models for Whole Page Presentation
by: Zhang, Zhenning, et al.
Published: (2024)