This page shows the most relevant public items for cog-rag, ranked by trend activity and review signal. Use weekly for fast changes, monthly for more stable patterns, and all-time for evergreen picks.
Blog • Feb 17, 2026 • Towardsai • Florian June
Traditional Retrieval-Augmented Generation (RAG) is becoming a commodity; the next frontier is 'Cog-RAG.' This post details a new architecture where an agentic 'brain' evaluates a query, identifies...
Paper • Mar 10, 2026 • arXiv • Md Nasir Uddin Shuvo, Md Aidul Islam, Md Mahade Hasan, Muhammad Waseem, Pekka Abrahamsson
This paper presents one of the first real-world experience reports of applying vibe coding in production environments. The authors analyze how LLM-based coding accelerates development while introdu...
Paper • Mar 6, 2026 • arXiv • Unknown
This paper proposes a schema-gated architecture that separates natural language reasoning from strict execution constraints in agentic AI systems. The framework allows large language models to gene...
Paper • Feb 5, 2026 • arXiv • Minghao Du, Yifan Sun, Zeyu Li
A-RAG proposes an agentic retrieval framework that exposes retrieval tools directly to large language models. Rather than treating retrieval as a static preprocessing step, the architecture allows ...
Paper • Feb 11, 2026 • arXiv • Pengcheng Zhou, Haochen Li, Zhiqiang Nie, JiaLe Chen, Qing Gong, Weizhen Zhang, Chun Yu
This paper introduces CogitoRAG, a cognitive-inspired retrieval-augmented generation framework designed to mimic human episodic memory and semantic gist formation. The system constructs a multi-dim...
Book • Jan 15, 2026 • O'Reilly • Michael Albada
This book provides a practical guide to designing and implementing AI agent systems using foundation models and modern orchestration techniques. It focuses heavily on multi-agent architectures, inc...
Book • Sep 24, 2024 • Princeton University Press • Arvind Narayanan, Sayash Kapoor
This book critically examines the limitations and hype surrounding AI systems, including generative coding tools. It provides frameworks for evaluating when AI systems are reliable and when they ar...
Paper • Sep 15, 2025 • arXiv • Veronica Pimenova, Sarah Fakhoury, Christian Bird, Margaret-Anne Storey, Madeline Endres
This qualitative study explores how developers interact with AI systems in vibe coding workflows. Through interviews and analysis of real-world usage, the authors identify key themes such as trust,...
Paper • Mar 11, 2026 • arXiv • Juhee Kim, Xiaoyuan Liu, Zhun Wang, Shi Qiu, Bo Li, Wenbo Guo, Dawn Song
This comprehensive survey analyzes the emerging security landscape surrounding agentic AI systems capable of autonomous reasoning, tool usage, and multi-step decision-making. The authors categorize...
Paper • Mar 9, 2026 • Nature Digital Medicine • H. L. Goh
This study evaluates the use of agentic AI systems to generate personalized preventive healthcare plans in Singapore’s national healthcare program. The system autonomously analyzes patient data, me...
Paper • Mar 4, 2026 • arXiv • Furkan Mumcu, Yasin Yilmaz
This research investigates robustness issues in agentic AI systems where autonomous agents interact with dynamic environments and external tools. The authors introduce adversarially-aligned Jacobia...
Paper • Mar 10, 2026 • arXiv • B. Lou
This paper explores the structural shift toward human–agentic AI collaboration systems where autonomous agents participate in complex decision processes. It analyzes the uncertainty introduced by a...
Paper • Mar 7, 2026 • arXiv • Junming Liu, Yuqi Li, Shiping Wen, Zhigang Zeng, Tingwen Huang
Hit-RAG addresses a key challenge in long-context retrieval systems: attention dilution caused by large volumes of retrieved evidence. The framework introduces a multi-stage preference alignment pi...
Paper • Feb 7, 2026 • arXiv • Xingliang Hou, Yuyan Liu, Qi Sun, Haoxiu Wang, Hao Hu, Shaoyi Du, Zhiqiang Tian
IGMiRAG introduces a cognitive-inspired retrieval framework that simulates intuition-driven reasoning over hierarchical knowledge graphs. The system constructs a heterogeneous hypergraph to represe...
Paper • Feb 14, 2026 • arXiv • Rui Yu, Tianyi Wang, Ruixia Liu, Yinglong Wang
PT-RAG proposes a structure-aware retrieval framework designed specifically for long academic documents. Traditional RAG pipelines flatten documents into chunks, which destroys the natural hierarch...
Paper • Nov 20, 2025 • arXiv • Hao Hu, Yifan Feng, Ruoxue Li, Rundong Xue
Cog-RAG introduces a cognitive-inspired dual-hypergraph architecture designed to capture both thematic and entity-level relationships within large document collections. The framework constructs two...
Book • Oct 21, 2025 • IT Revolution • Gene Kim, Steve Yegge
This flagship book defines the vibe coding paradigm, where developers shift from writing syntax to expressing intent through AI systems. It explains how GenAI, chat interfaces, and agents enable de...
Book • Nov 1, 2025 • O'Reilly • Addy Osmani
This book explores how developers evolve beyond basic vibe coding into structured AI-assisted engineering. It focuses on maintaining code quality, architecture, and long-term maintainability in AI-...
Book • Mar 17, 2026 • Manning • Roberto Infante
This book provides a hands-on guide to building agentic applications using modern frameworks such as LangChain and LangGraph. It covers prompt engineering, RAG systems, and multi-agent workflows fo...
Book • Dec 19, 2025 • Independently Published • Samuel R. Maddox
This book provides a hands-on engineering approach to building reliable multi-agent systems. It emphasizes coordination, orchestration, and communication between specialized agents. The author focu...
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