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@jerryjliu0: Our "agentic plus" extractor in LlamaParse is great for extracting out massive volumes of fields (e.g. 10k-100k+ fields…

X AI KOLs Following · 2026-08-15 Cached

Jerry Liu introduces ExtractBench and highlights the 'agentic plus' extractor in LlamaParse for handling massive volumes of fields in long documents, with benchmark results available on ExtractBench.

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#enterprise-documents

FinCacheServe: Dependency-Consistent Answer Reuse for Cost-Efficient RAG Serving over Mutable Enterprise Documents

arXiv cs.AI · 2026-07-31 Cached

FinCacheServe is a system for dependency-consistent answer reuse in RAG serving over mutable enterprise documents, using document versions, evidence fingerprints, and tool fingerprints to invalidate caches. Evaluations show it skips over 53% of LLM calls with zero stale outputs, reducing GPU cost compared to versioned semantic caching.

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#enterprise-documents

@jerryjliu0: Our team is at CVPR 2026 if you want to come say hi :)

X AI KOLs Following · 2026-06-04 Cached

Jerry Liu's team is presenting ParseBench, a comprehensive document understanding benchmark for VLMs, at CVPR 2026. The benchmark includes 2,000 pages of real-world enterprise documents with evaluation metrics for tables, charts, and visual grounding.

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#enterprise-documents

@jerryjliu0: We gave a full 90 minute workshop on how to build agentic workflows over your enterprise documents at @aiDotEngineer Si…

X AI KOLs Following · 2026-05-17 Cached

At AI Engineer Singapore, LlamaIndex presented a 90-minute workshop on building agentic workflows to extract information from enterprise PDFs; slides will be shared soon.

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