BestHub
Sign in
Architecture and Beyond
Architecture and Beyond
Apr 4, 2026 · Artificial Intelligence

How Claude Code Structures Its Memory: A Deep Dive into Multi‑Layered Agent Memory Design

This article dissects Claude Code's memory architecture, explaining its four distinct memory layers, file‑based long‑term storage, dynamic retrieval without embeddings, multi‑stage write paths, and session‑compression strategies, while highlighting design trade‑offs and practical takeaways for building robust AI agents.

AI ArchitectureAgent MemoryClaude Code
0 likes · 20 min read
How Claude Code Structures Its Memory: A Deep Dive into Multi‑Layered Agent Memory Design
PaperAgent
PaperAgent
Feb 3, 2026 · Artificial Intelligence

Relink: Turning GraphRAG into a Dynamic, Query‑Driven Knowledge Graph

Relink introduces a ‘reason‑and‑construct’ paradigm that builds knowledge‑graph paths during inference, combining a high‑precision factual graph with a high‑recall potential‑relation pool, using query‑driven dynamic path expansion and contrastive alignment to markedly improve multi‑hop QA performance and robustness to sparse knowledge.

Dynamic RetrievalGraphRAGKnowledge Graph
0 likes · 8 min read
Relink: Turning GraphRAG into a Dynamic, Query‑Driven Knowledge Graph
PaperAgent
PaperAgent
Jan 5, 2026 · Artificial Intelligence

How QuCo‑RAG Replaces Model Confidence with Objective Evidence to Cut Hallucinations

QuCo‑RAG introduces a dynamic retrieval‑augmented generation framework that quantifies uncertainty using pre‑training corpus statistics, replacing unreliable model confidence with objective frequency and co‑occurrence evidence, achieving millisecond‑level hallucination detection, superior multi‑hop QA performance, and cross‑model transferability across various LLMs.

Dynamic RetrievalHallucination DetectionLLM
0 likes · 9 min read
How QuCo‑RAG Replaces Model Confidence with Objective Evidence to Cut Hallucinations
Data Party THU
Data Party THU
Sep 11, 2025 · Artificial Intelligence

How ComRAG Revolutionizes Real‑Time Community QA with Dynamic Vector Stores

ComRAG tackles the static‑knowledge gaps, uneven QA quality, and storage explosion of community question‑answer platforms by integrating a static documentation vector store with dual dynamic CQA stores managed via a centroid‑based memory, delivering higher accuracy, lower latency, and scalable storage for industrial retrieval‑augmented generation.

Artificial IntelligenceCommunity QADynamic Retrieval
0 likes · 7 min read
How ComRAG Revolutionizes Real‑Time Community QA with Dynamic Vector Stores