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20242026
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cs.IR2025

DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management

Kai Yin, Xiangjue Dong, Chengkai Liu +4

Effective and efficient access to relevant information is essential for disaster management. However, no retrieval model is specialized for disaster management, and existing genera…

cs.IR2025

Towards An Efficient LLM Training Paradigm for CTR Prediction

Allen Lin, Renqin Cai, Yun He +5

Large Language Models (LLMs) have demonstrated tremendous potential as the next-generation ranking-based recommendation system. Many recent works have shown that LLMs can significa…

cs.IR2025

Federated Conversational Recommender System

Allen Lin, Jianling Wang, Ziwei Zhu +1

Conversational Recommender Systems (CRSs) have become increasingly popular as a powerful tool for providing personalized recommendation experiences. By directly engaging with users…

cs.IR2025

Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap

Weizhi Zhang, Yuanchen Bei, Liangwei Yang +15

Cold-start problem is one of the long-standing challenges in recommender systems, focusing on accurately modeling new or interaction-limited users or items to provide better recomm…

cs.IR2024

Countering Mainstream Bias via End-to-End Adaptive Local Learning

Jinhao Pan, Ziwei Zhu, Jianling Wang +2

Collaborative filtering (CF) based recommendations suffer from mainstream bias -- where mainstream users are favored over niche users, leading to poor recommendation quality for ma…