Hey everyone, Wanted to share some benchmark findings and get feedback on an architecture dilemma we ran into while testing RAG on dense corporate documents (specifically 300+ page SEC 10-Ks). When testing standard Vector RAG (dense embeddings + chunking): Cross-table reasoning breaks: Splitting documents into 500-token chunks frequently separates balance sheet tables from their clarifying footnote disclosures across different pages. HyDE hallucinated critical dates: We experimented with Hypothetical Document Embeddings (HyDE). The LLM hallucinated calendar year-ends (Dec 31) instead of the actual company fiscal year-end (June 30). Because the hypothetical answer had the wrong date, the vector search was mathematically pulled toward completely wrong quarters. **Compliance requires

  • 情报分类：技术价值
  • 命中依据：向量RAG局限与知识图谱实测分析
  • 来源：Reddit · SaaS
  • 原作者：/u/Training_Age26 https://www.reddit.com/user/Training_Age26
  • 发布时间：2026/9/12 14:47:24