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The Complexity of Tullock Contests
Yu He, Fan Yao, Yang Yu, Xiaoyun Qiu, Minming Li, Haifeng Xu
Last updated on Dec 9, 2024
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Single-Agent Poisoning Attacks Suffice to Ruin Multi-Agent Learning
Fan Yao, Yuwei Cheng, Ermin Wei, Haifeng Xu
Last updated on Oct 31, 2024
Strategic Filtering for Content Moderation: Free Speech or Free of Distortion?
Saba Ahmadi, Avrim Blum, Haifeng Xu, Fan Yao
Last updated on Oct 31, 2024
Learning from Imperfect Human Feedback: a Tale from Corruption-Robust Dueling
Yuwei Cheng, Fan Yao, Xuefeng Liu, Haifeng Xu
Last updated on Oct 31, 2024
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Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms
On User-Generated Content (UGC) platforms, recommendation algorithms significantly impact creators' motivation to produce content as …
Fan Yao, Yiming Liao, Jingzhou Liu, Shaoliang Nie, Qifan Wang, Haifeng Xu, Hongning Wang
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Human vs Generative AI in Content Creation Competition: Symbiosis or Conflict?
The advent of generative AI (GenAI) technology produces transformative impact on the content creation landscape, offering alternative …
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
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User Welfare Optimization in Recommender Systems with Competing Content Creators
Driven by the new economic opportunities created by the creator economy, an increasing number of content creators rely on and compete …
Fan Yao, Yiming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Jingzhou Liu, Qifan Wang, Haifeng Xu, Hongning Wang
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Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?
The past decade has witnessed the flourishing of a new profession as media content creators, who rely on revenue streams from online …
Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu
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How Bad is Top- Recommendation under Competing Content Creators?
Content creators compete for exposure on recommendation platforms, and such strategic behavior leads to a dynamic shift over the …
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
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Learning from a Learning User for Optimal Recommendations
Fan Yao, Chuanhao Li, Denis Nekepalov, Hongning Wang, Haifeng Xu
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