Hamza Najeeb

Chunk Size and Retrieval Depth Optimization in a Minimal Retrieval-Augmented Generation Pipeline

Retrieval‑augmented generation (RAG) links a large language model to a set of texts. But RAG works well only when two settings are right: how big each piece of text (a "chunk") is, and how many pieces the model reads. People often choose these by habit, not by data. In this study we tested how both settings change the...