Merge branch 'main' of https://github.com/RLHF-V/RLHF-V.github.io

index.html

@@ -363,7 +363,7 @@ <h2 class="title is-3">Abstract</h2>
                 <b style="font-family:Arial, Helvetica, sans-serif">Fine-Grained and Diverse Human Preference Data</b>: <span style="font-size: 95%;">We collect 1.4K fine-grained human feedback consisting of 3.7k pieces of segment-level corrections, covering hallucination types including objects (41.2%), positions (20.3%), numbers (16.5%), attributes (10%), actions (5.3%), and others (6.8%).</span>
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-                <b style="font-family:Arial, Helvetica, sans-serif">High Data Efficiency and Scalability</b>: <span style="font-size: 95%;">With just 1.4K annotated data, we achieved a 34.8% reduction in model hallucinations. Moreover, the decrease in hallucinations becomes more significant as more data used.</span>
+                <b style="font-family:Arial, Helvetica, sans-serif">High Data Efficiency and Scalability</b>: <span style="font-size: 95%;">With just 1.4K annotated data, we achieve a 34.8% reduction in model hallucinations. Moreover, the decrease in hallucinations becomes more significant as more data used.</span>
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                 <b style="font-family:Arial, Helvetica, sans-serif">Enhanced Performance and Computational Efficiency</b>: <span style="font-size: 95%;">Our fine-grained correctional human feedback data can better credit the desired behavior, allowing efficient training in 1 hour on 8 A100 GPUs to achieve promising results.</span>