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cs.LG2026
DiffNash: Finding Nash Equilibrium in High-Dimensional Continuous Action Spaces with Diffusion Policies
Haichuan Wang, Anagha Satish, Jiale Zheng +4
Computing equilibria in high-dimensional continuous games requires learning and representing rich, multi-modal strategy distributions, something conventional neural policies strugg…
cs.LG2026
Variance-Optimal Control Variates for Learning with Black-box Feedback
Zihao Zhao, Shuhan Zhang, Kai Wang
Modern models increasingly learn through black-box oracles such as humans, optimization solvers, and external tools that provide feedback without exposing their internal mechanisms…