TRIDENT improves compositional zero-shot recognition by using LLaVA hidden states as word embeddings and smoothing attribute labels with auxiliary adjectives generated by GPT-3.5.
Flamingo: a visual language model for few-shot learning
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Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot Learning
TRIDENT improves compositional zero-shot recognition by using LLaVA hidden states as word embeddings and smoothing attribute labels with auxiliary adjectives generated by GPT-3.5.