arXiv:2604.02578v1 Announce Type: cross
Abstract: Humans exhibit remarkable abilities to coordinate in groups. As large language models (LLMs) become more capable, it remains an open question whether they can demonstrate comparable adaptive coordinati…
arXiv:2504.03432v3 Announce Type: replace-cross
Abstract: Solving (Stampacchia) variational inequalities (SVIs) is a foundational problem at the heart of optimization. However, this expressivity comes at the cost of computational hardness. As a result…
arXiv:2406.02402v2 Announce Type: replace-cross
Abstract: We consider a practically motivated variant of the canonical online fair allocation problem: a decision-maker has a budget of perishable resources to allocate over a fixed number of rounds. Eac…
arXiv:2510.24906v2 Announce Type: replace-cross
Abstract: We consider the problem of payoff division in indivisible coalitional games, where the value of the grand coalition is a natural number. This number represents a certain quantity of indivisible…
arXiv:2604.00641v1 Announce Type: cross
Abstract: We propose a novel extension of the Bradley-Terry model to multiplayer games and adapt a recent algorithm by Newman [1] to our model. We demonstrate the use of our proposed method on synthetic datasets…
arXiv:2603.14867v3 Announce Type: replace
Abstract: Many strategic decision-making problems, such as environment design for warehouse robots, can be naturally formulated as bi-level reinforcement learning (RL), where a leader agent optimizes its objec…
arXiv:2506.06837v4 Announce Type: replace-cross
Abstract: The challenge of finding compromises between agent proposals is fundamental to AI subfields such as argumentation, mediation, and negotiation. Building on this tradition, Elkind et al. (2021) i…
arXiv:2603.28825v1 Announce Type: cross
Abstract: Artificial intelligence (AI) is widely promoted as a promising technological response to healthcare capacity and productivity pressures. Deployment of AI systems carries significant costs including ong…
arXiv:2603.26891v1 Announce Type: new
Abstract: AI arenas, which rank generative models from pairwise preferences of users, are a popular method for measuring the relative performance of models in the course of their organic use. Because rankings are …
arXiv:2603.27962v1 Announce Type: new
Abstract: Distributed learning has gained significant attention due to its advantages in scalability, privacy, and fault tolerance.In this paradigm, multiple agents collaboratively train a global model by exchangi…