arXiv AI

Online Fair Division with Budget Constraints

arXiv:2607. 23310v1 Announce Type: cross Abstract: We study an online variant of discrete fair division under generalized assignment budget constraints.

arXiv AI
Jul 21

Content Creation with Spillovers: An Incentive Design Approach

arXiv:2603. 14372v2 Announce Type: replace Abstract: The rise of AI amplifies the economic phenomenon of \emph{positive spillovers}: when creators contribute content that can be reused and adapted by LLMs, one creator's effort may improve the content quality of others through recombination.

By Sagi Ohayon, Boaz Taitler, Omer Ben-Porat
arXiv Machine Learning
Jul 30

Stable and Budget-Feasible Coalition Formation for Clustered Federated Learning: A Hedonic Potential-Game Approach

arXiv:2607. 26788v1 Announce Type: cross Abstract: Clustered federated learning benefits from organizing heterogeneous participants into coalitions that train coalition-specific models, but such clustering is sustainable only if participants prefer their assigned coalition and the required transfers are affordable.

By Cengis Hasan
arXiv Machine Learning
Jul 30

Parameterized Fair Resource Allocation under Diversity Constraints

arXiv:2607. 26485v1 Announce Type: cross Abstract: Resource allocation across multiple agent groups arises in many applications including e-commerce recommendation systems, housing assignment, and course allocation, and is commonly formulated as an optimization problem with diversity constraints to ensure group fairness.

By Keke Huang, Yik Yu Ng, Laks V. S. Lakshmanan, Xiaokui Xiao
arXiv Machine Learning
Jun 18

Fair Online Resource Allocation

arXiv:2606. 18679v1 Announce Type: cross Abstract: We study the problem of fair online resource allocation, motivated by applications such as refugee resettlement and airline scheduling, where agents arrive sequentially and must be assigned to facilities with limited capacities.

By Christopher En, Yuri Faenza, Andrea Lodi, Gonzalo Mu\~noz