MoDora introduces local-alignment aggregation, a Component-Correlation Tree, and question-type-aware retrieval to improve accuracy on semi-structured document QA by 5.97-61.07% over baselines.
Analyzing the efficacy of an llm- only approach for image-based document question answering
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Visual representations in VLMs converge quickly to stable low-complexity forms while text continues evolving, with task-dependent needs for sustained image token access.
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MoDora: Tree-Based Semi-Structured Document Analysis System
MoDora introduces local-alignment aggregation, a Component-Correlation Tree, and question-type-aware retrieval to improve accuracy on semi-structured document QA by 5.97-61.07% over baselines.
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Do Vision Language Models Need to Process Image Tokens?
Visual representations in VLMs converge quickly to stable low-complexity forms while text continues evolving, with task-dependent needs for sustained image token access.