AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work formalizes learnability as the success rate of converging to the global minimum, as a function of overparameterization, learning algorithm, student initialization distribution, and teacher geometry, and shows that differentially increasing the learning rate of the readout layer and decreasing the learning rat...
DiG-bench (Discovery in Games) is released, a new benchmark for discovering new knowledge with experimentation in controlled environments where the objective is unknown, which provides games at seven tiers of difficulty for AI agents.
It is shown that imbalanced learning of two conflicting copy tasks promotes in-context learning and improves the selectivity of refusal fine-tuning, suggesting that imbalanced pretraining curricula may be an important tool for promoting disentangled representations, with direct consequences for the precision and reliab...
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