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Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Oct 27, 2025 · Artificial Intelligence

Designing Effective Generation Modules for RAG: Prompt Engineering, Multi‑Document Fusion, and Hallucination Control

This article explains how to design and optimize the generation module of Retrieval‑Augmented Generation systems by building robust prompts, merging multi‑source information, controlling answer formats, and applying post‑generation verification to reduce hallucinations and improve enterprise‑grade performance.

AIGeneration ModuleHallucination Control
0 likes · 9 min read
Designing Effective Generation Modules for RAG: Prompt Engineering, Multi‑Document Fusion, and Hallucination Control
AntTech
AntTech
Sep 19, 2025 · Artificial Intelligence

How Reinforcement Learning Cuts Hallucinations in Large Language Models: Ant Insurance’s Proven Approach

Ant Insurance’s tech team leveraged reinforcement learning, focused data selection, and a multi‑dimensional reward system to dramatically reduce hallucinations in LLMs, achieving top‑rank performance on the HHEM leaderboard and robust improvements across instruction‑following and reasoning‑enhanced models.

Hallucination ControlLLMLLM-as-Judge
0 likes · 6 min read
How Reinforcement Learning Cuts Hallucinations in Large Language Models: Ant Insurance’s Proven Approach