AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
3 papers indexed here
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.
Running the same language model on different graphics processing unit (GPU) vendors can produce different logits, even when the model weights and inputs are the same. We analyze cross-vendor mismatch in two dense and two mixture-of-experts (MoE) models with five metric families, namely bitwise equality, logit differenc...
This work evaluates five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends, and finds that memory-backend choice matters more for content accuracy and permission-aware access fails in two distinct modes.
Experimental results show that ARSM maintains the task performance while simultaneously reducing token consumption, offering a practical, cost-effective route toward scalable autonomous agents for long-horizon tasks.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.