AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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20,463 papers
Rounded capacity cuts (RCCs) are among the most effective cuts for capacitated vehicle-routing relaxations, but exact separation is computationally prohibitive at scale. Existing heuristic and neural separators can be fast, but often fail to produce sufficiently many effective cuts within practical separation budgets....
This dissertation investigates whether Natural Language Processing (NLP) based semantic message prioritisation can improve the treatment of urgent disaster messages in opportunistic emergency communication, using the 2015 Nepal earthquake as a case study. TF IDF with Logistic Regression and BERT are used to classify so...
Vision-Language-Action (VLA) models offer a promising paradigm for general-purpose household robotics. However, inference and data-collection strategies that have been deployed in smaller-scale settings do not necessarily generalize to large-scale, diverse task suites. To address this gap, we conduct a systematic, pair...
This work introduces TERRA (Task-Oriented Edge Representation and Regional Aggregation), an edge-AI framework that combines task-oriented local inference, identity-free region-tagged reporting, and permutation-invariant regional evidence aggregation for regional inference under repetition-disjoint three-fold cross-vali...
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Metis is a bet that better data, better training methods and new architectures can buy what a bigger parameter count cannot, at a fraction of the cost. Metis-1.6 is its latest step: two language models built from scratch by a single researcher, Praxis (2.94B parameters, 0.46B active per pass) and Logos (10.23B paramete...
A six-module scanner that developed proof-of-concept attacks for each vulnerability, disclosed 10 medium- and high-severity cases to maintainers, and tested mitigations on the remaining cases prevented PoC attacks in all trials while preserving tested legitimate functionality.
The code, weights, evaluators, execution traces and cost accounting accompany the paper, where it is observed that the extra updates decrease the costs of the selected latent world-model trajectories for the updater, while the tasks that used to be successes become failures.
Deepfake detectors are almost always deployed as the single checkpoint that scored best on a validation split, yet the reliability of that choice is rarely measured. We measure it with PairCLIP-SWA, a single-backbone detector that adapts an OpenCLIP ViT-L/14 visual tower by progressive block unfreezing on a class-balan...
Initial results suggest that scaling off-policy experience is a promising approach to efficient direct visual RL, and a single-stage off-policy RL framework that scales experience collection without proportionally increasing visual computation is introduced.
Fine-tuning three Hamiltonian networks on QH9 in this way, which the authors call FermiScope, reduces the HOMO-LUMO gap error without increasing the element-wise error.
An AI developer often has several candidate versions of a system and can deploy a mixture of them, sending each request to a randomly chosen version, sending each request to a randomly chosen version, as in A/B testing, so the number of rejecting agents is minimized.
DeFT-RAG, a RAG framework built on three components, achieves the best accuracy among thirteen baselines with both gpt-4o-mini and Qwen3.6 as the backbone, while giving the LLM fewer input tokens than any other iterative method.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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