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Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 29, 2026 · Artificial Intelligence

Mastering RAG Prompt Engineering: Prevent Hallucinations and Boost Accuracy

This article dissects the unique challenges of RAG prompting, presents a systematic System/User Prompt design with strong constraints and citation requirements, compares constraint strengths with quantitative hallucination rates, and offers long‑context compression strategies and rigorous testing methods to ensure reliable LLM answers.

Context CompressionLLMRAG
0 likes · 19 min read
Mastering RAG Prompt Engineering: Prevent Hallucinations and Boost Accuracy
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Mar 11, 2026 · Industry Insights

GPT‑5.3 Cuts Hallucinations 27% and Gemini Flash‑Lite Slashes Costs – What It Means for AI’s Future

OpenAI and Google released GPT‑5.3 Instant and Gemini 3.1 Flash‑Lite on the same day, both emphasizing lower cost and smoother user experience rather than raw intelligence, with Google pricing its model at one‑eighth of flagship rates and OpenAI reporting a 27% hallucination reduction, signaling a shift in AI competition toward scalability and usability.

AI PricingAI industryGPT-5.3
0 likes · 5 min read
GPT‑5.3 Cuts Hallucinations 27% and Gemini Flash‑Lite Slashes Costs – What It Means for AI’s Future
Data Party THU
Data Party THU
Mar 8, 2026 · Artificial Intelligence

6 Practical Context‑Engineering Techniques to Tame RAG Hallucinations

This article explains why retrieval‑augmented generation (RAG) models often hallucinate, introduces the concept of context engineering, and details six practical techniques—including selective retrieval, context compression, hierarchical layout, dynamic query rewriting, memory management, and tool‑aware context—along with their trade‑offs and real‑world impact.

AIContext EngineeringLLM
0 likes · 23 min read
6 Practical Context‑Engineering Techniques to Tame RAG Hallucinations
PaperAgent
PaperAgent
Dec 12, 2025 · Artificial Intelligence

What Makes GPT‑5.2 and Gemini‑3‑Pro So Fast? Inside Their Key Features and Real‑World Tests

Gemini‑3‑pro’s surprise debut and OpenAI’s emergency release of GPT‑5.2 highlight a shift toward faster inference, deeper reasoning, and lower hallucination rates, with detailed performance metrics, three‑tier model options, extended context windows, and mixed community test results that reveal both strengths and shortcomings.

AI model performanceGPT-5.2Gemini-3-Pro
0 likes · 4 min read
What Makes GPT‑5.2 and Gemini‑3‑Pro So Fast? Inside Their Key Features and Real‑World Tests