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README.md
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@@ -333,7 +333,7 @@ We use the following _LLM-based metrics_:
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# Results
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In this section, we give the full experiment results, wherein the metrics of **Prec.**, **Rec.**, **F1.**, **R.L.**, **B.S.**, **Rel.**, **Eff.**, **Comp.**, **Pos.**, and **Avg.** represent image precision, image recall, image F1 score, rouge-l, BERTScore, image relevance, image effectiveness, comprehensive score, image position score, and average score, respectively. Specifically, the metric **Ord.** represents image ordering score.
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## Comprehensive performance results on MRAMG-Wit（Web Dataset）.
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| Framework | Model | MRAMG-Wit
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|------------|------------------------|-----------|-------|-------|-------|-------|-------|-------|-------|-------|-------|
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| | | Prec. | Rec. | F1 | R.L. | B.S. | Rel. | Eff. | Comp. | Pos. | Avg. |
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| Rule-Based | GPT-4o | 49.50 | 49.67 | 49.56 | 56.23 | 92.27 | 43.67 | 39.50 | 77.00 | 50.08 | 56.39 |
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# Results
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In this section, we give the full experiment results, wherein the metrics of **Prec.**, **Rec.**, **F1.**, **R.L.**, **B.S.**, **Rel.**, **Eff.**, **Comp.**, **Pos.**, and **Avg.** represent image precision, image recall, image F1 score, rouge-l, BERTScore, image relevance, image effectiveness, comprehensive score, image position score, and average score, respectively. Specifically, the metric **Ord.** represents image ordering score.
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## Comprehensive performance results on MRAMG-Wit（Web Dataset）.
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| Framework | Model | MRAMG-Wit |
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|------------|------------------------|-----------|-------|-------|-------|-------|-------|-------|-------|-------|-------|
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| | | Prec. | Rec. | F1 | R.L. | B.S. | Rel. | Eff. | Comp. | Pos. | Avg. |
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| Rule-Based | GPT-4o | 49.50 | 49.67 | 49.56 | 56.23 | 92.27 | 43.67 | 39.50 | 77.00 | 50.08 | 56.39 |
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