Cover Image

Localization Boosting for Growth Markets: Mitigating Cross-Locale Behavioral Bias in Learning-to-Rank

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Seran, Suryaa Veerabathiran, Kumar, Ashwin Naresh, King, Tracy Holloway, Zheng, Jing
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CRAB: Codebook Rebalancing for Bias Mitigation in Generative Recommendation
by: Fan, Zezhong, et al.
Published: (2026)

Semantic In-Domain Product Identification for Search Queries
by: Sharma, Sanat, et al.
Published: (2024)

SweRank: Software Issue Localization with Code Ranking
by: Reddy, Revanth Gangi, et al.
Published: (2025)

Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias
by: Cai, Miaomiao, et al.
Published: (2024)

Mitigating Propensity Bias of Large Language Models for Recommender Systems
by: Zhang, Guixian, et al.
Published: (2024)

Whole Page Unbiased Learning to Rank
by: Mao, Haitao, et al.
Published: (2022)

DenoiseRank: Learning to Rank by Diffusion Models
by: Wang, Ying, et al.
Published: (2026)

Vector Linking via Cross-Model Local Isometric Consistency
by: Chen, Ziying, et al.
Published: (2026)

FAIR-MATCH: A Multi-Objective Framework for Bias Mitigation in Reciprocal Dating Recommendations
by: Kotecha, Madhav
Published: (2025)

LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-based Ranking
by: Zeng, Yifan, et al.
Published: (2024)

Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting
by: Chen, Zeyuan, et al.
Published: (2024)

Optimizing Generative Ranking Relevance via Reinforcement Learning in Xiaohongshu Search
by: Zeng, Ziyang, et al.
Published: (2025)

Contextual Font Recommendations based on User Intent
by: Sharma, Sanat, et al.
Published: (2023)

SUMMIR: A Hallucination-Aware Framework for Ranking Sports Insights from LLMs
by: Kumar, Nitish, et al.
Published: (2026)

OG-Rank: Learning to Rank Fast and Slow with Uncertainty and Reward-Trend Guided Adaptive Exploration
by: Singh, Praphul, et al.
Published: (2025)

Take Care of Your Prompt Bias! Investigating and Mitigating Prompt Bias in Factual Knowledge Extraction
by: Xu, Ziyang, et al.
Published: (2024)

Contextual Dual Learning Algorithm with Listwise Distillation for Unbiased Learning to Rank
by: Yu, Lulu, et al.
Published: (2024)

Language Bias in Information Retrieval: The Nature of the Beast and Mitigation Methods
by: Yang, Jinrui, et al.
Published: (2025)

Personalized Behavior-Aware Transformer for Multi-Behavior Sequential Recommendation
by: Su, Jiajie, et al.
Published: (2024)

LLM-Aligned Geographic Item Tokenization for Local-Life Recommendation
by: Jiang, Hao, et al.
Published: (2025)

Text-to-SQL Calibration: No Need to Ask -- Just Rescale Model Probabilities
by: Ramachandran, Ashwin, et al.
Published: (2024)

SemaCDR: LLM-Powered Transferable Semantics for Cross-Domain Sequential Recommendation
by: Zhang, Chunxu, et al.
Published: (2026)

Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction
by: Wu, Yi, et al.
Published: (2024)

The Ranking Blind Spot: Decision Hijacking in LLM-based Text Ranking
by: Qian, Yaoyao, et al.
Published: (2025)

Bias vs Bias -- Dawn of Justice: A Fair Fight in Recommendation Systems
by: Kheya, Tahsin Alamgir, et al.
Published: (2025)

CausalRec: A CausalBoost Attention Model for Sequential Recommendation
by: Hou, Yunbo, et al.
Published: (2025)

SeqUDA-Rec: Sequential User Behavior Enhanced Recommendation via Global Unsupervised Data Augmentation for Personalized Content Marketing
by: Luo, Ruihan, et al.
Published: (2025)

OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service
by: Wei, Zhipeng, et al.
Published: (2025)

DualView: Adaptive Local-Global Fusion for Multi-Hop Document Reranking
by: Zhang, Litong, et al.
Published: (2026)

Debiased Contrastive Representation Learning for Mitigating Dual Biases in Recommender Systems
by: Huang, Zhirong, et al.
Published: (2024)

OrdRankBen: A Novel Ranking Benchmark for Ordinal Relevance in NLP
by: Wang, Yan, et al.
Published: (2025)

Reformulate, Retrieve, Localize: Agents for Repository-Level Bug Localization
by: Caumartin, Genevieve, et al.
Published: (2025)

PRECTR-V2:Unified Relevance-CTR Framework with Cross-User Preference Mining, Exposure Bias Correction, and LLM-Distilled Encoder Optimization
by: Cao, Shuzhi, et al.
Published: (2026)

MemX: A Local-First Long-Term Memory System for AI Assistants
by: Sun, Lizheng
Published: (2026)

Dynamic Forgetting and Spatio-Temporal Periodic Interest Modeling for Local-Life Service Recommendation
by: Hu, Zhaoyu, et al.
Published: (2025)

TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou
by: Si, Zihua, et al.
Published: (2024)

Agentic Personalisation of Cross-Channel Marketing Experiences
by: Abboud, Sami, et al.
Published: (2025)

CiteBART: Learning to Generate Citations for Local Citation Recommendation
by: Çelik, Ege Yiğit, et al.
Published: (2024)

Unbiased Learning to Rank Meets Reality: Lessons from Baidu's Large-Scale Search Dataset
by: Hager, Philipp, et al.
Published: (2024)

Autoregressive Ranking: Bridging the Gap Between Dual and Cross Encoders
by: Rozonoyer, Benjamin, et al.
Published: (2026)