Papers by Haomiao Tang

1 papers
Modeling Uncertainty in Composed Image Retrieval via Probabilistic Embeddings (2025.acl-long)

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Challenge: Composed Image Retrieval (CIR) combines text and reference images to search for images . metric learning methods that focus on point embeddings fail to capture uncertainty in input data .
Approach: They propose a framework that captures uncertainty in images and queries by Gaussian distributions in latent space rather than fixed points.
Outcome: Experiments show that the proposed framework quantifies quality and semantic uncertainties . it can handle polysemy and ambiguity in search intentions, authors say .

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