Image de couverture de livre

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank (Extended Abstract)

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Hager, Philipp, Zoeter, Onno, de Rijke, Maarten
Format:	Preprint
Publié:	2025
Sujets:	Information Retrieval
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank
par: Hager, Philipp, et autres
Publié: (2025)

Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset
par: Hager, Philipp, et autres
Publié: (2024)

CLAX: Fast and Flexible Neural Click Models in JAX
par: Hager, Philipp, et autres
Publié: (2025)

Understanding the Effects of the Baidu-ULTR Logging Policy on Two-Tower Models
par: de Haan, Morris, et autres
Publié: (2024)

Towards Two-Stage Counterfactual Learning to Rank
par: Gupta, Shashank, et autres
Publié: (2025)

An Offline Metric for the Debiasedness of Click Models
par: Deffayet, Romain, et autres
Publié: (2023)

RankingSHAP -- Listwise Feature Attribution Explanations for Ranking Models
par: Heuss, Maria, et autres
Publié: (2024)

Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
par: Gupta, Shashank, et autres
Publié: (2024)

RankTower: A Synergistic Framework for Enhancing Two-Tower Pre-Ranking Model
par: Yan, YaChen, et autres
Publié: (2024)

Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees
par: Kang, Jingwei, et autres
Publié: (2024)

Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank
par: Gupta, Shashank, et autres
Publié: (2024)

The Impact of Group Membership Bias on the Quality and Fairness of Exposure in Ranking
par: Vardasbi, Ali, et autres
Publié: (2023)

Understanding Visual Saliency of Outlier Items in Product Search
par: Sarvi, Fatemeh, et autres
Publié: (2025)

Attack-in-the-Chain: Bootstrapping Large Language Models for Attacks Against Black-box Neural Ranking Models
par: Liu, Yu-An, et autres
Publié: (2024)

A Learnable Fully Interacted Two-Tower Model for Pre-Ranking System
par: Xiong, Chao, et autres
Publié: (2025)

HIT Model: A Hierarchical Interaction-Enhanced Two-Tower Model for Pre-Ranking Systems
par: Yang, Haoqiang, et autres
Publié: (2025)

Addressing Personalized Bias for Unbiased Learning to Rank
par: Niu, Zechun, et autres
Publié: (2025)

ERASE -- A Real-World Aligned Benchmark for Unlearning in Recommender Systems
par: Lubitzsch, Pierre, et autres
Publié: (2026)

A First Look at Selection Bias in Preference Elicitation for Recommendation
par: Gupta, Shashank, et autres
Publié: (2024)

Revisiting Language Models in Neural News Recommender Systems
par: Zhao, Yuyue, et autres
Publié: (2025)

InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization
par: Jin, Jiarui, et autres
Publié: (2024)

Whole Page Unbiased Learning to Rank
par: Mao, Haitao, et autres
Publié: (2022)

Document Similarity Enhanced IPS Estimation for Unbiased Learning to Rank
par: Liang, Zeyan, et autres
Publié: (2025)

Unbiased Top-k Learning to Rank with Causal Likelihood Decomposition
par: Zhao, Haiyuan, et autres
Publié: (2022)

One Backpropagation in Two Tower Recommendation Models
par: Chen, Erjia, et autres
Publié: (2024)

Rethinking Click Models in Light of Carousel Interfaces: Theory-Based Categorization and Design of Click Models
par: Kang, Jingwei, et autres
Publié: (2025)

Listwise Generative Retrieval Models via a Sequential Learning Process
par: Tang, Yubao, et autres
Publié: (2024)

Reason to Retrieve: Enhancing Query Understanding through Decomposition and Interpretation
par: Zhong, Yunfei, et autres
Publié: (2025)

Repeat-bias-aware Optimization of Beyond-accuracy Metrics for Next Basket Recommendation
par: Liu, Yuanna, et autres
Publié: (2025)

Robust Information Retrieval
par: Liu, Yu-An, et autres
Publié: (2024)

Contrastive Learning for Diversity-Aware Product Recommendations in Retail
par: Karlis, Vasileios, et autres
Publié: (2026)

Multi-granular Adversarial Attacks against Black-box Neural Ranking Models
par: Liu, Yu-An, et autres
Publié: (2024)

Understanding Accuracy-Fairness Trade-offs in Re-ranking through Elasticity in Economics
par: Xu, Chen, et autres
Publié: (2025)

Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMs
par: Siro, Clemencia, et autres
Publié: (2024)

Orcheo: A Modular Full-Stack Platform for Conversational Search
par: Jiang, Shaojie, et autres
Publié: (2026)

Multi-Step Semantic Reasoning in Generative Retrieval
par: Dong, Steven, et autres
Publié: (2026)

On the Robustness of Generative Information Retrieval Models
par: Liu, Yu-An, et autres
Publié: (2024)

Controlled Retrieval-augmented Context Evaluation for Long-form RAG
par: Ju, Jia-Huei, et autres
Publié: (2025)

Are Large Language Models Good at Utility Judgments?
par: Zhang, Hengran, et autres
Publié: (2024)

Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)
par: Li, Yuchen, et autres
Publié: (2024)