most citedHuman vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?

3 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Strategic Filtering for Content Moderation: Free Speech or Free of Distortion?

Saba Ahmadi, Avrim Blum, Haifeng Xu +1

User-generated content (UGC) on social media platforms is vulnerable to incitements and manipulations, necessitating effective regulations. To address these challenges, those platf…

cs.GT2024

The Complexity of Tullock Contests

Yu He, Fan Yao, Yang Yu +3

Despite the extensive literature on Tullock contests, computational results for the general model with heterogeneous contestants remain scarce. This paper studies the algorithmic c…

cs.GT2024★ 1 cited

Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms

Fan Yao, Yiming Liao, Jingzhou Liu +4

On User-Generated Content (UGC) platforms, recommendation algorithms significantly impact creators' motivation to produce content as they compete for algorithmically allocated user…

cs.LG2024

Learning from Imperfect Human Feedback: a Tale from Corruption-Robust Dueling

Yuwei Cheng, Fan Yao, Xuefeng Liu +1

This paper studies Learning from Imperfect Human Feedback (LIHF), addressing the potential irrationality or imperfect perception when learning from comparative human feedback. Buil…

cs.IR2024

User Welfare Optimization in Recommender Systems with Competing Content Creators

Fan Yao, Yiming Liao, Mingzhe Wu +6

Driven by the new economic opportunities created by the creator economy, an increasing number of content creators rely on and compete for revenue generated from online content reco…

cs.GT2024★ 3 cited

Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?

Fan Yao, Chuanhao Li, Denis Nekipelov +2

The advent of generative AI (GenAI) technology produces transformative impact on the content creation landscape, offering alternative approaches to produce diverse, high-quality co…

cs.LG2024

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tianze Ren +2

To enhance the efficiency and practicality of federated bandit learning, recent advances have introduced incentives to motivate communication among clients, where a client particip…