arXiv:2606. 12260v1 Announce Type: cross Abstract: How can we design a market of human-generated content for use in training AI models that both enables technological progress and preserves individual incentives for high-quality content creation?
By Yan Dai, Maryam Farboodi, Negin Golrezaei, Sepehr Shahshahani
arXiv:2607. 23310v1 Announce Type: cross Abstract: We study an online variant of discrete fair division under generalized assignment budget constraints.
By Saar Cohen, Nicholas Teh, Paul W. Goldberg, Michael J. Wooldridge
The paper investigates the compatibility of envy-freeness and equitability in fair division, focusing on both indivisible goods and chores. It shows that the relaxed notions EF1+EQ1 may not exist even for normalized additive valuations, but provides an algorithm that finds an EF1+EQ1 allocation for up to seven agents with binary goods. For chores, the authors prove that a stronger EFX+EQX guarantee always exists, regardless of normalization, and they also explore cross-notion ex‑ante and ex‑post fairness guarantees.
By Hadi Hosseini, Shraddha Pathak, Lirong Xia, Chengkai Zhang
arXiv:2601. 17944v2 Announce Type: replace-cross Abstract: We study repeated allocation of shared resources among agents with time-varying demands and capped linear utilities.
By Seyed Majid Zahedi, Rupert Freeman
arXiv:2607. 00641v1 Announce Type: cross Abstract: Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings.
By Luyang Zhang, Xirui Jiang, Junwei Deng, Beibei Li, Jiaqi W. Ma, Chris Donahue
arXiv:2608.24400v1 Announce Type: cross
Abstract: We study multilevel fair resource allocation with tree-structured hierarchical relations among agents. At each level, the problem can be viewed local...
By Maxime Lucet, Nawal Benabbou, Aur\'elie Beynier, Nicolas Maudet