Knowledge Integration

2 items

RESEARCHarXiv CS.LG·5/7/2026

Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search

This paper introduces Structured Progressive Knowledge Activation (SPARK) to address the challenge of integrating architectural knowledge in LLM-driven Neural Architecture Search (NAS). SPARK mitigates "functional entanglement" by enabling factor-conditioned editing, leading to more targeted and reliable architecture modifications.

Neural Architecture Search machine learning Knowledge Integration large language models

DOCDEV.to AI·4/25/2026

Introduction to RAG for LLMs: Sparse (Lexical) RAG and Dense RAG (Semantic Vector Search)

LLMs struggle with up-to-date information due to knowledge cutoffs, which can lead to hallucinations. Retrieval Augmented Generation (RAG) is introduced as a vital external solution to integrate current data and overcome these limitations.

LLMs AI limitations RAG Knowledge Integration