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The image features a grouped bar chart titled "Direct Comparison of GPT-4o-mini and GPT-o1 Across Metrics (with Task Names)" with the caption "Figure 3: Comparison of GPT-4o-mini and GPT-o1 performance across all datasets and metrics for the long-text generation task." The vertical axis represents "Scores" ranging from 0.00 to 0.25 with increments of 0.05, and the horizontal axis lists "Datasets and Metrics" across twelve paired comparisons for GPT-4o-mini and GPT-o1, respectively: Task 1 (ROUGE-1) at ~0.19 vs. ~0.18; Task 1 (ROUGE-L) at ~0.12 vs. ~0.12; Task 1 (METEOR) at ~0.26 vs. ~0.25; Task 2 (ROUGE-1) at ~0.20 vs. ~0.18; Task 2 (ROUGE-L) at ~0.15 vs. ~0.14; Task 2 (METEOR) at ~0.21 vs. ~0.20; Task 3 (ROUGE-1) at ~0.13 vs. ~0.13; Task 3 (ROUGE-L) at ~0.20 vs. ~0.19; Task 3 (METEOR) at ~0.14 vs. ~0.13; Task 4 (ROUGE-1) at ~0.20 vs. ~0.18; Task 4 (ROUGE-L) at ~0.15 vs. ~0.14; and Task 4 (METEOR) at ~0.17 vs. ~0.17.
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The illustration gives information about comparison between GPT-40 and GPT-01 across different metrics. Overall, GPT-40 outperforms and achieve highest scores from GPT-01. The task 1 meteor was dominant candidate among all other dataset, where both GPT-40 and 01 are on the top in scores. In contrast, ROUGE-L gains scores hovering around 0.19 for both artificial intelligence models.
It is quite evident from the bar graph that in task 1, GPT-1 does not score higher comparing with other version. Rouge-1 score is 0.18 and 0.19 approximately for GPT-mini and GPT-1 respectively. In contrast, task 2 has no longer strikingly different results from task 1. The meteor achieves higher scores approximately 0.21 tailoring behind Rouge-1 and Rouge-L.
Furthermore, a similar pattern is seen in task 3 and task 4. In task 3, ROUGE-L obtains higher scores around 0.20 compared with meteor and ROUGE-1. Meanwhile, In task 4, all gain approximately same marks, but ROUGE-1 is still leading the trend.
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