Papers by Ellen Yi-Ge

1 papers
DRUM: Learning Demonstration Retriever for Large MUlti-modal Models (2025.acl-srw)

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Challenge: Recent studies have shown that large language models (LLMs) have impressive capabilities in dealing with new tasks with the help of in-context learning (ICL).
Approach: They propose to concate the image and text embeddings to enhance the retrieval performance of a visual-language task and to calculate a list-wise ranking loss for training the embeddable model.
Outcome: The proposed framework fine-tunes the CLIP embedding model to better meet the needs of the large vision-language models.

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