AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes Abstract Token Curriculum (ATC), a novel curriculum learning framework that elicits effective continuous intermediate representations without direct supervision or manual scratchpad design and shows ATC's effectiveness on graph reachability and arithmetic learning tasks.
It is shown that this gating mechanism causes SSMs to first learn an in-weights"memorization"solution, while delaying, or even preventing, convergence to a correct in-context learning solution, and that gating is often beneficial for improving generalization to long sequence lengths.
It is suggested that using standard CoT prompting increasingly acts as a source of distraction as models grow stronger, because standard CoT prompting also demands style adaptation, formatting compliance, and potentially undesired contextualization, which can distract models from the core reasoning task.
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