32 citations · 34 across the 7 of their papers we have counts for
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cs.IR2024
Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
Sunhao Dai, Weihao Liu, Yuqi Zhou +6
The proliferation of Large Language Models (LLMs) has led to an influx of AI-generated content (AIGC) on the internet, transforming the corpus of Information Retrieval (IR) systems…
cs.IR2024★ 1 cited
Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop
Yuqi Zhou, Sunhao Dai, Liang Pang +4
Recommender systems are essential for information access, allowing users to present their content for recommendation. With the rise of large language models (LLMs), AI-generated co…
cs.IR2024★ 1 cited
Guaranteeing Accuracy and Fairness under Fluctuating User Traffic: A Bankruptcy-Inspired Re-ranking Approach
Xiaopeng Ye, Chen Xu, Jun Xu +3
Out of sustainable and economical considerations, two-sided recommendation platforms must satisfy the needs of both users and providers. Previous studies often show that the two si…