Papers with score smoothing

1 papers
FLEUR: An Explainable Reference-Free Evaluation Metric for Image Captioning Using a Large Multimodal Model (2024.acl-long)

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Challenge: Existing image captioning evaluation metrics do not provide an explanation for the assigned numerical score.
Approach: They propose an explainable reference-free metric to provide an explanation for captions . they introduce score smoothing to align as closely as possible with human judgment .
Outcome: The proposed metric achieves high correlations with human judgment across image captioning evaluation benchmarks and is publicly available at https://github.com/Yebin46/FLEUR.

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