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llamaindex.ai · newsletter
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Existing benchmarks for schema-guided document extraction weren’t built for workflows where agents act on the output. They measure only a slice of the task and miss the failure modes that matter in production. So our applied research team built our own.
Join Simon Suo, CTO and Co-Gounder of LlamaIndex, for a technical walkthrough of ExtractBench, a new benchmark evaluating 14 frontier systems across 370 enterprise documents, 67 document types, and 4,800+ pages. He’ll cover the real-world failure modes that shaped it, the trade-offs between VLMs and coding agents, and what testing top systems revealed.
You will learn:
How document extraction evaluation has evolved, and where existing benchmarks fall short
What makes document extraction hard and how to measure that difficulty
How cost scales with accuracy across VLMs, coding agents and specialized APIs
How to structure robust extraction evals around your own documents and schemas
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Best regards,
LlamaIndex Team
LlamaIndex, 405 Howard Street, San Francisco, California 94105, United States
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