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Wu Shixiong's Large Model Academy
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Wu Shixiong's Large Model Academy

We continuously share large‑model know‑how, helping you master core skills—LLM, RAG, fine‑tuning, deployment—from zero to job offer, tailored for career‑switchers, autumn recruiters, and those seeking stable large‑model positions.

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Recent Articles

Latest from Wu Shixiong's Large Model Academy

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Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 19, 2026 · Artificial Intelligence

Making LLM Answers Trustworthy: Citation Attribution and Hallucination Detection

This article explains why simple prompt‑based citation is insufficient for Retrieval‑Augmented Generation, introduces a sentence‑level attribution pipeline, combines semantic similarity with NLI verification, and presents practical hallucination detection and structured JSON output to ensure answer reliability.

Hallucination DetectionLLM reliabilityNLI
0 likes · 10 min read
Making LLM Answers Trustworthy: Citation Attribution and Hallucination Detection
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 17, 2026 · Artificial Intelligence

Mastering Chunk Splitting for RAG: From Fixed Length to Semantic Segmentation

Chunk splitting, a critical yet often overlooked step in RAG pipelines, dramatically impacts retrieval recall and LLM output quality; this guide walks through three evolution stages—from naive fixed‑length splits to sentence‑aware overlaps and finally semantic, structure‑driven segmentation—complete with code, experiments, and practical pitfalls.

ChunkingLLMRAG
0 likes · 15 min read
Mastering Chunk Splitting for RAG: From Fixed Length to Semantic Segmentation
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 13, 2026 · Artificial Intelligence

Why Every RAG System Needs Smart Query Understanding and Routing

The article explains how diverse user queries in a RAG‑based insurance system require intent classification, entity extraction, and multi‑path routing to choose between vector search, calculation, database lookup, or chit‑chat, and outlines practical rule‑ML‑LLM hybrid solutions with safety safeguards.

LLMRAGentity extraction
0 likes · 11 min read
Why Every RAG System Needs Smart Query Understanding and Routing
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 12, 2026 · Artificial Intelligence

How to Build Cross-Session Memory for RAG Chatbots: Short‑Term vs Long‑Term Strategies

This article explains the role of memory modules in Retrieval‑Augmented Generation systems, compares short‑term and long‑term memory techniques, outlines storage and retrieval methods, discusses management strategies like forgetting and deduplication, and compares LangChain and LlamaIndex implementations for practical deployment.

LLMLangChainLlamaIndex
0 likes · 11 min read
How to Build Cross-Session Memory for RAG Chatbots: Short‑Term vs Long‑Term Strategies
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 11, 2026 · Artificial Intelligence

Taming Hallucinations and Multi‑Turn Failures in RAG Systems

This article breaks down the final‑mile challenges of Retrieval‑Augmented Generation—hallucinations, broken multi‑turn dialogue, prompt design, citation, and feedback loops—and provides concrete, layered solutions ranging from hard‑coded prompts and few‑shot examples to query rewriting, history management, post‑processing filters, and self‑check mechanisms.

Hallucination mitigationRAGcitation
0 likes · 15 min read
Taming Hallucinations and Multi‑Turn Failures in RAG Systems
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 10, 2026 · Artificial Intelligence

RRF vs Weighted Sum in RAG: Boost Retrieval, Solve Timeliness & Interview Challenges

This article explains why Reciprocal Rank Fusion often outperforms weighted‑sum fusion in Retrieval‑Augmented Generation, presents a three‑layer approach to keep knowledge bases timely, discusses HyDE’s cost‑benefit trade‑offs, and offers concrete interview‑ready answers for common RAG follow‑up questions.

HyDEHybrid RetrievalInterview Tips
0 likes · 13 min read
RRF vs Weighted Sum in RAG: Boost Retrieval, Solve Timeliness & Interview Challenges
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 7, 2026 · Artificial Intelligence

Mastering Offline Document Parsing for RAG: From PDFs to Multimodal Knowledge Bases

This article provides a comprehensive guide to offline document parsing for Retrieval‑Augmented Generation, covering multi‑format extraction, layout analysis, OCR pitfalls, chunking strategies, hierarchical metadata tagging, and how these steps directly affect retrieval accuracy and overall RAG performance.

Document ParsingRAGmetadata
0 likes · 14 min read
Mastering Offline Document Parsing for RAG: From PDFs to Multimodal Knowledge Bases