AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 5 of 36 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.
This work introduces InfiMed2, a family of 4B and 27B generalist medical multimodal foundation models built around stage-aware data design, and curates a 55.68B-token corpus that combines broad clinical knowledge with context-rich biomedical visual evidence through source-specific processing.
Findings show that routing drift alone is insufficient evidence of routing failure, and source-informed corrections must be judged by their task-level intervention effects, and proposes Selective Router Repair as a case study, and finds that source-specialist token-likelihood advantages do not reliably identify benefic...
An efficient graph-transformer operator, named PhysGTO, is shown for learning physical dynamics through explicit manifold embeddings in both physical and latent spaces, showing strong flexibility, scalability, and generalization across diverse physical systems.
MedPIC-Bench makes conditional rule application measurable and highlights the limitations of static medication-safety accuracy for assessing patient-specific reliability among medical-specific LLMs, whose average CF performance trails that of general LLMs.
DART (Decoded Attention over Recurrent sTates), which retains the chunk state contributions produced by the Mamba-2 chunked scan as chunk state memories, decodes token-conditioned keys and values from these memories, and performs state-memory attention (SMA) over the resulting KV pairs.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.