Consensus Entropy measures inter-VLM output agreement to verify OCR reliability and enable self-improving ensembles, yielding 42.1% F1 gains over single-model judging.
Mini-internvl: a flexible-transfer pocket multi-modal model with 5% parameters and 90% perfor- mance.Visual Intelligence, 2(1):1–17, 2024
2 Pith papers cite this work. Polarity classification is still indexing.
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Linear probing reveals a gap between internal representations and responses in LVLMs for visual document understanding, with task information encoded more linearly in intermediate layers than the final layer, and fine-tuning those layers narrows the gap.
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Consensus Entropy: Harnessing Multi-VLM Agreement for Self-Verifying and Self-Improving OCR
Consensus Entropy measures inter-VLM output agreement to verify OCR reliability and enable self-improving ensembles, yielding 42.1% F1 gains over single-model judging.
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Responses Fall Short of Understanding: Revealing the Gap between Internal Representations and Responses in Visual Document Understanding
Linear probing reveals a gap between internal representations and responses in LVLMs for visual document understanding, with task information encoded more linearly in intermediate layers than the final layer, and fine-tuning those layers narrows the gap.