Building Document Structure with Loop Engineering: Recovering a PDF’s Outline from Body Typography for RAG
A structured RAG pipeline needs the document’s table of contents: retrieval scopes by section, and the chunker cuts on heading boundaries instead of mid-sentence. A paper exported straight from LaTeX has no native outline and no printed contents page, so there is no toc_df for the pipeline to read. The headings are still right there on the body, section by section, bigger and bolder than the text around them.
- ▪A structured RAG pipeline needs the document’s table of contents: retrieval scopes by section, and the chunker cuts on heading boundaries instead of mid-sentence.
- ▪A paper exported straight from LaTeX has no native outline and no printed contents page, so there is no toc_df for the pipeline to read.
- ▪The headings are still right there on the body, section by section, bigger and bolder than the text around them.
Towards Data Science files mainly under ai. We currently carry 117 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/building-document-structure-with-loop-engineering-recovering-a-pdfs-outline-from-body-typography-for-rag/ |
| Publication time | Wed, 05 Aug 2026 12:00:00 +0000 |
| Retrieval time | 2026-08-05T12:05:41.578Z |
| Last seen | 2026-08-05T12:05:41.578Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 0_DgYPwyA7Av · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Large Language Model Building Document Structure with Loop Engineering: Recovering a PDF’s Outline from Body Typography for RAG Enterprise Document Intelligence [Vol.1 #5octies] – Rules propose, LLM validates: six deterministic signals on span-level typography surface heading candidates, one bounded loop keeps the real ones, and the same toc_df drops back into the RAG pipeline angela shi Aug 5, 2026 26 min read Share Photo by icon0.com, via Pexels. A structured RAG pipeline needs the document’s table of contents: retrieval scopes by section, and the chunker cuts on heading boundaries instead of mid-sentence. But some documents don’t have one. A paper exported straight from LaTeX has no native outline and no printed contents page, so there is no toc_df for the pipeline to read.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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