AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 3 of 32 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.
Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existing harness-model co-evolution approaches improve both components, yet often treat trajectories produced during harness search as an undifferentiated replay buffer. This...
Opera is presented, a verbal critic framework that treats each correction as a persistent note, followed until the diagnosed problem is resolved, and achieves the highest mean resolve rate among competitive critic baselines on all three benchmarks.
DarwinX is introduced, which treats self-evolution as selection over a population of harnesses with the model frozen: a preserve-and-extend contract admits only variants that extend coverage without regressing, an archive keeps alternative lineages for recombination, and failure-, teacher-, and self-derived evidence sh...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.