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20202025
most citedRethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

4 citations · 22 across the 19 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference

Kendong Liu, Zhiyu Zhu, Chuanhao Li +3

In this paper, we make the first attempt to align diffusion models for image inpainting with human aesthetic standards via a reinforcement learning framework, significantly improvi…

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.LG2024

Federated Linear Contextual Bandits with Heterogeneous Clients

Ethan Blaser, Chuanhao Li, Hongning Wang

The demand for collaborative and private bandit learning across multiple agents is surging due to the growing quantity of data generated from distributed systems. Federated bandit…

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…