AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 4 of 29 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
These findings establish open System One models as a promising zero shot baseline for medical AI, combining competitive predictive performance with low computational cost and efficient local calibration, and introduce a lightweight, two parameter recalibration method.
Contemporary Genomic Foundation Models (GFMs) rely on a DNA-as-a-string paradigm that employs masked token prediction objectives for pretraining. However, this abstraction does not explicitly model the biochemical, structural, and physical properties essential to biological function. Many molecular properties can be es...
A reference-aligned diploid encoding for single-nucleotide variants (SNVs) and short insertions and deletions (indels) and unphased and phase-retaining tokenizers that accept phased genotypes and convert them to single-sequence diploid representation are introduced.
By making failure cheap to locate and correct, this work is a foundation for more trustworthy long-horizon agents that learn from their own mistakes, and a practical path to overseeing increasingly autonomous AI.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.