AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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W2S-OPD is introduced, a simple yet effective OPD framework that improves the strong student by distilling from multiple weak models, and outperforms OPD, enables the student to surpass the domain teacher, and keeps improving the student even when every supervision source is weaker.
Masked diffusion language models (dLLMs) generate text by iteratively denoising masked tokens with bidirectional attention. Extending reasoning across generation chunks normally requires keeping earlier generated text in context. We ask whether a dLLM can instead continue reasoning after that text is cleared, using onl...
This work proposes a reinforcement learning (RL) fine-tuning framework that treats EHR foundation models as generative policies over patient trajectories, and finds that RL fine-tuning consistently improves over pre-trained backbones and strong baselines.
GFlowRL, a streamlined GFlowNet-style RL algorithm that removes the auxiliary partition network entirely while preserving the reward-distribution-matching objective, is proposed, and is the first GFlowNet-style RL algorithm to scale stably across both dense and sparse architectures.
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