ivila-row-layoutlm-finetuned-s2vl-v2
| Property | Value |
|---|---|
| Developer | Allen AI |
| Model Type | LayoutLM |
| Primary Task | Table Row Detection |
| Model URL | Hugging Face |
What is ivila-row-layoutlm-finetuned-s2vl-v2?
This model represents a specialized version of LayoutLM that has been fine-tuned specifically for detecting and understanding table rows in scientific documents. Built by Allen AI, it combines visual and textual information to effectively process document layouts with a focus on tabular data.
Implementation Details
The model builds upon the LayoutLM architecture, which is designed to understand document layout and text simultaneously. This version has been specifically optimized for the S2VL dataset, focusing on scientific document analysis.
- Built on LayoutLM architecture
- Fine-tuned for table row detection
- Optimized for scientific documents
- Incorporates both visual and textual features
Core Capabilities
- Table structure recognition
- Row-level information extraction
- Document layout understanding
- Scientific document processing
- Multi-modal analysis of tables
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in table row detection within scientific documents, utilizing both visual and textual information through the LayoutLM architecture. Its fine-tuning on the S2VL dataset makes it particularly effective for scientific document analysis.
Q: What are the recommended use cases?
The model is best suited for applications involving scientific document processing, particularly where table extraction and understanding is required. This includes academic paper analysis, data extraction from research documents, and automated table parsing systems.
