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Update app.py
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app.py
CHANGED
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@@ -16,15 +16,31 @@ with gr.Blocks(css="""
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}
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""") as demo:
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gr.HTML("""
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<div align="center">
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<
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<
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</div>
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<br>
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</div>
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""")
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gr.HTML("""
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<div style="display: flex; justify-content: center; gap: 8px; flex-wrap: wrap;">
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<a href="https://arxiv.org/pdf/2505.05315">
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@@ -68,9 +84,7 @@ training.
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gr.Image("figs/codetable.png", label="Framework", show_label=False, elem_id="my-img")
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gr.HTML("""
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<div align="center">
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<
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<h3>Part 2:Fractured Chain-of-Thought (Fractured Chain-of-Thought Reasoning) 🌟
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</div>
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<br>
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</div>
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""")
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@@ -144,6 +158,11 @@ This joint sampling strategy leverages the complementary strengths of each dimen
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}
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```
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""")
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if __name__ == "__main__":
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}
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""") as demo:
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gr.HTML("""
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<div align="center" style="padding: 10px;">
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<a href="#part1" style="margin-right: 20px; font-size: 18px;">🔹 Part 1: Elastic Reasoning</a>
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<a href="#part2" style="font-size: 18px;">🔹 Part 2: Fractured CoT</a>
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</div>
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""")
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gr.HTML("""
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<div align="center">
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<h1 id="top">Efficient Reasoning</h1>
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<p>
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This demo is structured in two parts, each showcasing a recent advancement in scalable and efficient reasoning with large language models:
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<br><br>
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<b>Part 1:</b> <i>Elastic Reasoning</i> focuses on budget-aware generation by explicitly separating thinking and solution stages.
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<br>
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<b>Part 2:</b> <i>Fractured Chain-of-Thought</i> explores sampling efficiency by fragmenting the reasoning process along multiple dimensions.
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</p>
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<br>
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</div>
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""")
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gr.HTML("""
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<div align="center">
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<h3 id="part1">Part 1: Elastic Reasoning 🌟</h3>
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<br>
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</div>
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""")
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gr.HTML("""
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<div style="display: flex; justify-content: center; gap: 8px; flex-wrap: wrap;">
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<a href="https://arxiv.org/pdf/2505.05315">
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gr.Image("figs/codetable.png", label="Framework", show_label=False, elem_id="my-img")
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gr.HTML("""
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<div align="center">
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<h3 id="part2">Part 2: Fractured Chain-of-Thought 🌟</h3>
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<br>
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</div>
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""")
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}
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```
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""")
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gr.HTML("""
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<div align="center" style="margin-top: 30px;">
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<a href="#top" style="font-size: 16px;">⬆️ Back to Top</a>
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</div>
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""")
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if __name__ == "__main__":
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