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Introduces H^2SD, a hybrid hindsight self-distillation framework that improves RLVR by using the teacher model differently for successful and failed trajectories, achieving better reasoning performance.
This paper presents a hybrid approach combining dynamic programming and constraint programming to solve the Partial Shop Scheduling Problem, demonstrating the viability of integrating both paradigms despite not outperforming pure CP solvers.
This paper proposes a hybrid method combining Wave Function Collapse (WFC) and reinforcement learning to generate game levels that are both visually satisfying and playable, using WFC constraints to guide the RL agent.