Specialization Factor (SF): Continuous Depth Modulation for Distributed LLM Networks
Abstract
Prior art declaration for the Specialization Factor (SF), a continuous parameter in [0,1] that modulates LLM analytical depth in real-time without retraining. Applicable to distributed multi-node inference networks (AOED-RAM). Model-agnostic, runtime-modifiable, per-node configurable.
Fields of Study & Subjects
Advanced Neural Network Applications
Topic Modeling
Domain Adaptation and Few-Shot Learning
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 4 March 2026
- Language
- EN
- Document type
- Preprint