AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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T2T(Thickening-to-Thinning), a dynamic reward framework inspired by human learning processes, implements a dual-phase mechanism that significantly outperforms standard GRPO and recent baselines, achieving superior performance.
This work reformulates the implicit reward of sampled-token OPD based on trajectory correctness, then applies a ReLU gating mechanism to ensure that correct trajectories receive non-negative rewards and incorrect ones receive non-positive rewards, making it readily combinable with any policy gradient algorithm, such as...
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