Papers with LLaVE-7B

1 papers
LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning (2025.findings-emnlp)

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Challenge: Existing LMM-based embedding models exhibit a high degree of overlap in similarity distribution between positive and negative pairs, making it challenging to distinguish hard negative pairs effectively.
Approach: They propose a framework that improves the embedding model's representation learning for negative pairs based on their discriminative difficulty.
Outcome: The proposed framework improves the embedding model's representation learning for negative pairs based on their discriminative difficulty.

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