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    <title>PyPI recent updates for truescore</title>
    <link>https://pypi.org/project/truescore/</link>
    <description>Recent updates to the Python Package Index for truescore</description>
    <language>en</language>    <item>
      <title>0.7.3</title>
      <link>https://pypi.org/project/truescore/0.7.3/</link>
      <description>Statistically valid evaluation for LLM-judged benchmarks: bias-corrected scores, honest intervals, defensible comparisons</description>
<author>saifpunjwani1230@gmail.com</author>      <pubDate>Mon, 27 Jul 2026 08:18:19 GMT</pubDate>
    </item>    <item>
      <title>0.7.2</title>
      <link>https://pypi.org/project/truescore/0.7.2/</link>
      <description>Statistically valid evaluation for LLM-judged benchmarks: bias-corrected scores, honest intervals, defensible comparisons</description>
<author>saifpunjwani1230@gmail.com</author>      <pubDate>Mon, 27 Jul 2026 07:57:55 GMT</pubDate>
    </item>    <item>
      <title>0.7.1</title>
      <link>https://pypi.org/project/truescore/0.7.1/</link>
      <description>Statistically valid evaluation for LLM-judged benchmarks: bias-corrected scores, honest intervals, defensible comparisons</description>
<author>saifpunjwani1230@gmail.com</author>      <pubDate>Mon, 27 Jul 2026 07:44:20 GMT</pubDate>
    </item>    <item>
      <title>0.7.0</title>
      <link>https://pypi.org/project/truescore/0.7.0/</link>
      <description>Statistically valid evaluation for LLM-judged benchmarks: bias-corrected scores, honest intervals, defensible comparisons</description>
<author>saifpunjwani1230@gmail.com</author>      <pubDate>Mon, 27 Jul 2026 06:54:04 GMT</pubDate>
    </item>    <item>
      <title>0.6.0</title>
      <link>https://pypi.org/project/truescore/0.6.0/</link>
      <description>Statistically valid evaluation for LLM-judged benchmarks: bias-corrected scores, honest intervals, defensible comparisons</description>
<author>saifpunjwani1230@gmail.com</author>      <pubDate>Mon, 27 Jul 2026 00:31:05 GMT</pubDate>
    </item>    <item>
      <title>0.5.0</title>
      <link>https://pypi.org/project/truescore/0.5.0/</link>
      <description>Statistically valid evaluation for LLM-judged benchmarks: bias-corrected scores, honest intervals, defensible comparisons</description>
<author>saifpunjwani1230@gmail.com</author>      <pubDate>Sun, 26 Jul 2026 22:52:54 GMT</pubDate>
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