7,093 high-difficulty samples form a benchmark for large multimodal models focused on real-world document processing. It covers 5 major OCR-centric tracks and emphasizes practical enterprise tasks and underrepresented corner cases. The dataset was created by Eioss and was last updated on Hugging Face in May 2026.
Use Cases
- Benchmarking OCR model performance on high-difficulty samples.
- Training models for enterprise document processing tasks.
- Evaluating model robustness on underrepresented corner cases.
- Developing multimodal systems for real-world document analysis.
Strengths
- 7,093 samples provide a substantial testbed for evaluation.
- Focus on high-difficulty and corner cases addresses a gap in prior benchmarks.
- Covers 5 distinct OCR-centric tracks for multi-faceted assessment.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- Eioss via Hugging Face.
- Freshness
- Last updated 2026-05-08 18:23:36.