#citation verification
115 related articles
·3 min
Andrew Ng's Prompting Course: Four Core Gaps Between AI Beginners and Power Users
Andrew Ng's AI Prompting for Everyone course reveals four key gaps between AI beginners and power users: deep thinking tasks, context, neutral prompting, and iterative workflows.
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·4 min
HAMAS Multi-Agent Framework in Practice: A Guide to Building 5 AI Personas Working in Harmony
Learn how to build a multi-Agent AI team with the HAMAS framework: 5 role configurations, Skill mechanisms, gradient model scheduling, and solutions for AI hallucination and deception.
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·3 min
ARS Framework from Shanghai Jiao Tong University: Enabling Automated AI Research with Trustworthy Conclusions
Shanghai Jiao Tong University's ARS open-source framework solves trustworthiness challenges in autonomous AI research with evidence traceability and independent verification. Papers completed via ARS have been accepted at academic conferences.
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·3 min
5 Daily Claude Code Tips: Let AI Interrogate You Instead
5 daily Claude Code tips: Grill Me for requirements, Brainstorming for architecture, Writing Plan for execution, TDD for testing, and Debugging for precise fixes — a complete AI coding workflow.
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·3 min
Building a Cold Chain Logistics Optimization Research Project with Codex: A Complete Workflow from Scratch to PDF Paper
Learn how to use OpenAI Codex to build a complete cold chain logistics optimization research project from scratch, including simulated annealing implementation, experiments, figures, and LaTeX paper compilation.
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·3 min
Connecting Zotero MCP to Claude and Codex: A Deep Writing Workflow Powered by Your Local Reference Library
Learn how to connect your local Zotero library to Claude and Codex via Zotero MCP for AI-assisted academic writing with real citations, PDF-to-Markdown optimization, and ARS command workflows.
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·2 min
NotebookLM Anniversary Data Revealed: The Source-Driven AI Revolution Behind 1.5 Billion Notebooks
Google NotebookLM celebrates its anniversary with 1.5 billion notebooks, audio overviews, and slides created. A deep dive into its source-driven AI design, core features, and future direction.
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·3 min
Claude Code Ultra Code in Practice: One Person Orchestrating 100+ Agents in Parallel Development
Learn how to use Claude Code's Ultra Code and Dynamic Workflow to orchestrate 100+ Agents in parallel, with Deep Research demos, token-saving tips, and workflow reuse methods.
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·2 min
Advanced Claude Code: 5 Skill Techniques for Building Efficient AI Workflows
5 advanced Claude Code Skill techniques — Prompt Optimizer, Deep Interview, Real Plan, Code Simplifier, and Skill Creator — to build reusable AI workflows that reduce rework and boost precision.
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·4 min
The Age of Information Fragmentation: How to Identify Low-Quality Content and Link Rot
Exploring content identification challenges in the fragmented information age, analyzing low-density content, link rot, and their impact on AI processing, with practical multi-source verification strategies.
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Deep Dives·4 min
AI Hallucinations: Why Large Language Models Inevitably "Make Things Up" and How to Deal With It
Deep dive into AI hallucination's three root causes: training objective flaws, exposure bias, and probabilistic generation. Covers classification and practical mitigation strategies including RAG.
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Deep Dives
How the Higgs Field Gives Particles Ma…
·4 min
How the Higgs Field Gives Particles Mass: From Electroweak Unification to Symmetry Breaking
A deep dive into how the Higgs field gives particles mass, from electroweak unification to symmetry breaking, the discovery of the Higgs boson, and the critical phase transition in the early universe.
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Deep Dives
The Vacuum Energy Crisis: Why Quantum …
·4 min
The Vacuum Energy Crisis: Why Quantum Field Theory's Prediction Exceeds Dark Energy by 10^120
QFT's vacuum energy prediction exceeds dark energy observations by 10^120 — physics' worst prediction. Explore the cosmological constant problem, why even optimistic estimates leave a 10^60 gap, and the theoretical solutions being pursued.
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Tech Frontiers·3 min
GPT 5.5 Instant Deep Dive: How It Tackles AI Hallucinations for Trustworthy Real-World Deployment
Deep dive into GPT 5.5 Instant's core breakthrough: dramatically reducing AI hallucination rates while achieving low latency and high accuracy. Explore real-world applications in legal, medical, and financial sectors.
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Tutorials·4 min
Practical Guide to Building a Local AI Knowledge Base with Qwen3.5 + RAGFlow + Ollama
Step-by-step guide to building a local RAG knowledge base using RAGFlow, Ollama, and LM Studio with Docker, covering Embedding model deployment and network troubleshooting for private AI Q&A.
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Product Reviews·3 min
Mavis Hands-On Review: Multi-Agent Collaboration vs. Single Agent — A Comprehensive Comparison in Academic Research and Web Development
In-depth review of Mavis multi-agent platform across academic retrieval, literature review, and web development. Multi-agent mode significantly outperforms single agents in accuracy and reliability.
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Tutorials·3 min
Spring AI + MCP Protocol in Practice: Tool Calling, Security Authentication, and Enterprise Deployment
Deep dive into Spring AI and MCP protocol integration, covering tool calling, OAuth security, horizontal scaling, and context optimization for enterprise AI Agent services.
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Product Reviews·3 min
Devin 2.0 In-Depth Review: Is the $20/Month AI Coding Agent Actually Worth It?
In-depth analysis of Devin 2.0: dropped from $500 to $20/month, 12x efficiency in code migration, but only 15% completion on complex tasks. Real test data on use cases and limitations.
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Tutorials·3 min
Open-Source Multi-Agent Intelligent Diagnostic System: Deep Dive into MCP + RAG + Skill Routing Architecture
Deep dive into an open-source multi-Agent diagnostic system built on modified OneCall, featuring MCP real-time interaction, RAG-enhanced Q&A, and Skill routing to minimize Token consumption.
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Tutorials·3 min
Enterprise RAG Implementation: Architecture Principles and Production-Grade Optimization Guide
Complete guide to enterprise RAG architecture covering data indexing, vectorization, and retrieval optimization. Practical insights on chunking strategies, hybrid retrieval, and hallucination control for production-grade LLM applications.
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