AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is found that model pairs can learn to communicate the secret using only one bit of feedback indicating whether the receiver inferred it correctly, during inference with fixed parameters and no supplied codebook or encoding examples.
BOW is introduced, an RL framework that instead trains models to produce self-contained, neutral, and comprehensive descriptions of the plausible next-word space, and human evaluation shows that BOW-Reg produces broader next-word reasoning trajectories, while direct next-word-prediction evaluation shows that these traj...
This work proves a PAC-Bayes bound guaranteeing that a dictionary extracted from successful trajectories has bounded expected description length on future successful behavior, and introduces ReuseRL, which grounds agentic RL in the Minimum Description Length (MDL) principle.
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