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    Jerry Liu Pledges Open Benchmarks for Document Parsing

    LlamaIndex founder highlights commitment to reproducible evaluation tools ParseBench and ExtractBench.

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    6 Sources, 26d ago, first seen 26d ago

    TLDR

    Jerry Liu, co-founder and CEO of LlamaIndex, posted that unlike other players in the OCR space the company does not block competitors from its platform. He stated a commitment to open reproducible benchmarks for document parsing and extraction on ParseBench and ExtractBench. The linked ParseBench site describes evaluation across tables charts content faithfulness semantic formatting and visual grounding. The ExtractBench site describes a schema-guided extraction benchmark for enterprise documents where every system fills the same JSON schema from the same document.

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    6 Sources, first seen 26d ago

    Combined views

    15.9K

    6 Sources, first seen 26d ago

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    22 comments
    63 saves
    21 reposts

    Sentiment

    Positiveβ€”β€”Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    6 Sources

    @jerryjliu0Unlike other players in the OCR space, we don't block our competitors from accessing our platform. We're also fully committed towards open, reproducible benchmarks for document parsing and extraction - on ParseBench and ExtractBench respectively. It's important to give the industry a sense of how the pareto frontier of accuracy and cost evolves over time. ParseBench and ExtractBench are fully open, maintained benchmarks that we're constantly adding every day (e.g. 3.8 flash, fable 5.1, r-1) Sometimes we make mistakes on benchmarking, and we take into account your feedback on how to fix and improve the results! You can access both benchmarks from the links below, which also give you access to Github/Huggingface and more. ParseBench: https://www.parsebench.ai/ ExtractBench: https://www.extractbench.ai/ In the meantime, if you're looking to ship doc OCR workloads to production, we'd be happy to help you benchmark LlamaParse against other solutions you're considering over your data and compare the results. Sign up here: https://cloud.llamaindex.ai/
    @imaanxsultan@jerryjliu0 class and transparency is the only way to win !! πŸš€

    6 Sources

    @jerryjliu0Unlike other players in the OCR space, we don't block our competitors from accessing our platform. We're also fully committed towards open, reproducible benchmarks for document parsing and extraction - on ParseBench and ExtractBench respectively. It's important to give the industry a sense of how the pareto frontier of accuracy and cost evolves over time. ParseBench and ExtractBench are fully open, maintained benchmarks that we're constantly adding every day (e.g. 3.8 flash, fable 5.1, r-1) Sometimes we make mistakes on benchmarking, and we take into account your feedback on how to fix and improve the results! You can access both benchmarks from the links below, which also give you access to Github/Huggingface and more. ParseBench: https://www.parsebench.ai/ ExtractBench: https://www.extractbench.ai/ In the meantime, if you're looking to ship doc OCR workloads to production, we'd be happy to help you benchmark LlamaParse against other solutions you're considering over your data and compare the results. Sign up here: https://cloud.llamaindex.ai/
    @imaanxsultan@jerryjliu0 class and transparency is the only way to win !! πŸš€