AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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GURI (Gray-box Uncertainty Representations with Identity), a lightweight gray-box hallucination detector that combines candidate-token probabilities with per-token vector identifiers that exposes which alternatives the model considered while preserving the accessibility and transferability of the gray-box setting.
This work studies an activation alignment, a map from a source model's layerwise activations to a target's, and factors this map into a layer map, whose output is an explicit target-by-source matrix that can be extracted and inspected, and a layer-shared feature map between hidden spaces.
A weight space network (or metanetwork) takes the weights of another neural network as input and predicts properties of it. Most prior work trains such models on input networks of one or a few fixed sizes and evaluates them in-distribution. The few attempts at out-of-distribution size generalization remain limited in s...
Weight-space networks operate directly on parameters of other neural networks, enabling tasks such as predicting model properties, editing trained models, and generating weights. Weight-space symmetries such as neuron permutations make equivariance a key design principle. However, existing equivariant weight-space arch...
This work parameterize a flow-matching velocity field with a permutation-equivariant Graph Meta Network, enabling direct learning from independently trained networks without alignment, and shows how permutation equivariance enables learning from diverse collections of independently trained networks without permutation...
This work studies when finite probe-based representations are sufficient for learning neural functionals, establishes general identification and universality results for probing, and shows that using intermediate hidden representations can provide significantly more informative representations than relying only on fina...
UniProbe is introduced, a lightweight, unified, learnable detector that models a frozen LVLM's heterogeneous computational trace from a single forward pass and achieves state-of-the-art token-level and object-hallucination detection.
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