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Document images paired with question/answer pairs that require **implicit reasoning** over the document — deriving, cross-referencing, or computing a value — rather than plain OCR transcription. This is the held-out test split used by the [ImplicitIR Benchmark](https://github.com/VXRealLimited/ImplicitIR-Benchmark) eval harness; the reasoning-annotated training splits (with raw field data and derivation traces, used for SFT/GRPO) live in the [ImplicitIR](https://github.com/VXRealLimited/ImplicitIR) training repo.
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Most document images are real-world documents sourced from the Unikie benchmark (MIT licensed); the `Synthetic` category is procedurally generated and not derived from Unikie. This dataset (questions, answers, and synthetic images) is released under CC-BY-4.0; the `images/real/` subset remains additionally subject to Unikie's MIT license and attribution requirement.
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## Dataset structure
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Document images paired with question/answer pairs that require **implicit reasoning** over the document — deriving, cross-referencing, or computing a value — rather than plain OCR transcription. This is the held-out test split used by the [ImplicitIR Benchmark](https://github.com/VXRealLimited/ImplicitIR-Benchmark) eval harness; the reasoning-annotated training splits (with raw field data and derivation traces, used for SFT/GRPO) live in the [ImplicitIR](https://github.com/VXRealLimited/ImplicitIR) training repo.
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Most document images are real-world documents sourced from the Unikie benchmark (MIT licensed); the `Synthetic` category is procedurally generated and not derived from Unikie. This dataset (questions, answers, and synthetic images) is released under CC-BY-4.0; the `images/real/` subset remains additionally subject to Unikie's MIT license and attribution requirement.
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## Dataset structure
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