The Vision-Language Alignment Problem
How vision-language models align visual and text representations using contrastive learning, cross-modal attention, and CLIP-style training.
5 min readConcept
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vision-language
Explore machine learning concepts related to vision-language. Clear explanations and practical insights.
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Concepts Found
Concepts Related to vision-language
The Modality Gap
The modality gap in CLIP and vision-language models: why image and text embeddings occupy separate regions despite contrastive training.
6 min readConcept
Multimodal Scaling Laws
Discover how multimodal vision-language models like CLIP, ALIGN, and LLaVA scale with data, parameters, and compute following Chinchilla-style power laws.
5 min readConcept
Vision-Language Adapters: Parameter-Efficient Multimodal Fine-tuning
Master LoRA, bottleneck adapters, and prefix tuning for parameter-efficient fine-tuning of vision-language models like LLaVA with minimal compute and memory.
8 min readConcept