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Models/RORE (GeoLayoutLM)

RORE (GeoLayoutLM)

Reported on 7 benchmarks across 4 tasks · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing7 results

Entity LinkingonEC-FUNSD
F1· 2024-09-29
87.42
SOTA
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672
Key Information ExtractiononCORD
F1· 2024-09-29
98.52
SOTA
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672
Relation ExtractiononFUNSD
F1· 2024-09-29
88.46
best: 90.81 (LayoutLMv3 large EM + BBO + RSF)
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672
Entity LinkingonFUNSD
F1· 2024-09-29
88.46
best: 89.45 (GeoLayoutLM)
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672
Semantic entity labelingonEC-FUNSD
F1· 2024-09-29
84.34
best: 84.53 (RORE (LayoutLMv3-large))
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672
Semantic entity labelingonFUNSD
F1· 2024-09-29
91.84
best: 93.2 (LayoutMask (large))
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672
Key Information ExtractiononSROIE
F1· 2024-09-29
96.97
best: 97.81 (LayoutLMv2LARGE (Excluding OCR mismatch))
Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding arXiv:2409.19672