SPARK: Self-Play with Asymmetric Reward from Knowledge Graphs
概要
arXiv:2605.05546v1 Announce Type: new Abstract: Self-play reinforcement learning has shown strong performance in domains with formally verifiable structure, such as mathematics and coding, where both problem generation and reward computation can be grounded in explicit rules. Extending this paradig…
