What is the current consensus on the best algorithms for optimizing vector search accuracy when dealing with messy PDF documents?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What is the current consensus on the best algorithms for optimizing vector search accuracy when dealing with messy PDF documents?
3 real searches · 1 real-search pass
2025 2026 RAG PDF document retrieval benchmark hybrid search reranking layout-aware chunking OCR researchGoogle ↗
OBSERVEDReason
best practices PDF RAG retrieval hybrid BM25 dense reranking ColBERT late interaction 2025Google ↗
OBSERVEDInstruction
layout-aware document parsing PDF tables RAG retrieval accuracy benchmark 2025Google ↗
OBSERVEDReason
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (3)
Classes come from the query-classifier (a local Laya model). 3 of 3 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT3 real searches · gpt-6
2025 2026 RAG PDF document retrieval benchmark hybrid search reranking layout-aware chunking OCR research Google ↗
best practices PDF RAG retrieval hybrid BM25 dense reranking ColBERT late interaction 2025 Google ↗
layout-aware document parsing PDF tables RAG retrieval accuracy benchmark 2025 Google ↗
- From PDF to RAG-Ready: Evaluating Document Conversion Frameworks for Domain-Specific Question Answering · doi.org
- From PDF to RAG-Ready: Evaluating Document Conversion Frameworks for Domain-Specific Question Answering · arxiv.org
- GitHub - opendatalab/OmniDocBench: [CVPR 2025] A Comprehensive Benchmark for Document Parsing and Evaluation · github.com
- OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations · mlanthology.org
- From BM25 to Corrective RAG: Benchmarking Retrieval Strategies for Text-and-Table Documents · arxiv.org
- Paper page - From BM25 to Corrective RAG: Benchmarking Retrieval Strategies for Text-and-Table Documents · huggingface.co
- From PDF to RAG-Ready: Evaluating Document Conversion Frameworks for Domain-Specific Question Answering · mdpi.com
- LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding · aclanthology.org
- A Systematic Literature Review of Retrieval-Augmented Generation: Techniques, Metrics, and Challenges · mdpi.com
- Evaluating Lexical, Dense, and Hybrid Retrieval Pipelines for RAG | IEEE Conference Publication · ieeexplore.ieee.org
Queries
3 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
2025 2026 RAG PDF document retrieval benchmark hybrid search reranking layout-aware chunking OCR research OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
best practices PDF RAG retrieval hybrid BM25 dense reranking ColBERT late interaction 2025 OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 | |
layout-aware document parsing PDF tables RAG retrieval accuracy benchmark 2025 OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |