An Examination of the Robustness of Reference-Free Image Captioning Evaluation Metrics (2024.findings-eacl)
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| Challenge: | Recent studies have proposed reference-free evaluations of image captions . however, these approaches are restrictive and favor captions with similar vocabulary but different meanings. |
| Approach: | They propose to use reference-free metrics to evaluate image captions . they propose to combine lexical overlap and semantics to identify fine-grained errors . |
| Outcome: | The proposed metrics struggle to identify fine-grained errors, the authors show . CLIPScore, UMIC, and PAC-S are sensitive to variations in image-relevant objects mentioned in the caption . |
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