AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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On-policy distillation (OPD) provides dense token-level supervision on student-generated trajectories. Although OPD performs strongly when teacher and student belong to the same model family, we find that its effectiveness degrades in cross-family settings even after tokenizer alignment, with substantially stronger ext...
Focused On-demand Visual Evidence Adaptation is proposed, a cache-friendly approach that builds a reusable visual memory and dynamically retrieves a bounded subset for a draft state and demonstrates that state-conditioned evidence retrieval is an effective alternative to reusing a fixed visual representation throughout...
CoRe-MoE is proposed, a Compact Reusable MoE framework for parameter-efficient continual multimodal instruction tuning that improves final average performance over the strongest competing baseline by up to 5.90 points, while using less than 1% of the trainable parameters required by sequential LoRA for later tasks.
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