Flatness Preference Optimization (FlatPO) improves multimodal PEFT generalization by flattening a small set of sharp dimensions that dominate performance.
Consistency-guided prompt learning for vision-language models
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cs.CV 3years
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GAPL anchors text prompts to second-order Gram matrix statistics to improve vision-language model adaptation across domains.
VACSR reformulates cross-modal similarity learning as variational inference with regularization to mitigate binary annotation compression in image-text tasks.
citing papers explorer
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5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning
Flatness Preference Optimization (FlatPO) improves multimodal PEFT generalization by flattening a small set of sharp dimensions that dominate performance.
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Gram-Anchored Prompt Learning for Vision-Language Models via Second-Order Statistics
GAPL anchors text prompts to second-order Gram matrix statistics to improve vision-language model adaptation across domains.
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Variational Adapter for Cross-modal Similarity Representation
VACSR reformulates cross-modal similarity learning as variational inference with regularization to mitigate binary annotation compression in image-text tasks.