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Reproducing zero-shot temporal image classification results on the MS-CXR-T benchmark

Open Wentap123 opened this issue 1 year ago • 2 comments

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I have made modifications to the code hi-ml-multimodal/test_multimodal/vlp/test_zero_shot_classification.py in order to replicate the zero-shot temporal image classification results on the MS-CXR-T benchmark. However, the performance is lower compared to the aforementioned results. The details are as follows:

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While using the code, I attempted different seeds, but obtained the same result. This is because it solely utilizes the function "get_similarity_score_from_raw_data()" to derive a score, which differs from the section "F.4. Auto-regressive prompting for zero-shot temporal image classification" in the paper titled "Learning to Exploit Temporal Structure for Biomedical Vision–Language Processing."

Could you provide me with some insights regarding this matter?

Wentap123 avatar May 07 '24 04:05 Wentap123

same question

pepperbubble avatar Oct 18 '24 09:10 pepperbubble