arXiv cs.CL
· Papers
Models for minimalist RAG: B1ade 335M Embedding and 1B Parameter Small Language Models
arXiv:2607.27506v1 Announce Type: new Abstract: Language and embedding models used in RAG systems are conventionally assumed to require large-scale pretraining and explicit grounding supervision. We present B1ade, an efficient RAG architecture comprising two purpose-built components: a compact embedding model and a pur