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    <title>PyPI recent updates for lsynth</title>
    <link>https://pypi.org/project/lsynth/</link>
    <description>Recent updates to the Python Package Index for lsynth</description>
    <language>en</language>    <item>
      <title>0.1.27</title>
      <link>https://pypi.org/project/lsynth/0.1.27/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Tue, 16 Dec 2025 18:54:23 GMT</pubDate>
    </item>    <item>
      <title>0.1.26</title>
      <link>https://pypi.org/project/lsynth/0.1.26/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Tue, 16 Dec 2025 18:54:16 GMT</pubDate>
    </item>    <item>
      <title>0.1.25</title>
      <link>https://pypi.org/project/lsynth/0.1.25/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Tue, 16 Dec 2025 18:40:01 GMT</pubDate>
    </item>    <item>
      <title>0.1.24</title>
      <link>https://pypi.org/project/lsynth/0.1.24/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Tue, 16 Dec 2025 17:18:24 GMT</pubDate>
    </item>    <item>
      <title>0.1.23</title>
      <link>https://pypi.org/project/lsynth/0.1.23/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 04:34:23 GMT</pubDate>
    </item>    <item>
      <title>0.1.22</title>
      <link>https://pypi.org/project/lsynth/0.1.22/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 04:32:07 GMT</pubDate>
    </item>    <item>
      <title>0.1.21</title>
      <link>https://pypi.org/project/lsynth/0.1.21/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 04:17:00 GMT</pubDate>
    </item>    <item>
      <title>0.1.20</title>
      <link>https://pypi.org/project/lsynth/0.1.20/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 04:15:58 GMT</pubDate>
    </item>    <item>
      <title>0.1.19</title>
      <link>https://pypi.org/project/lsynth/0.1.19/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 03:58:53 GMT</pubDate>
    </item>    <item>
      <title>0.1.18</title>
      <link>https://pypi.org/project/lsynth/0.1.18/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 03:29:07 GMT</pubDate>
    </item>    <item>
      <title>0.1.17</title>
      <link>https://pypi.org/project/lsynth/0.1.17/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 03:28:02 GMT</pubDate>
    </item>    <item>
      <title>0.1.16</title>
      <link>https://pypi.org/project/lsynth/0.1.16/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 03:25:49 GMT</pubDate>
    </item>    <item>
      <title>0.1.15</title>
      <link>https://pypi.org/project/lsynth/0.1.15/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 02:56:13 GMT</pubDate>
    </item>    <item>
      <title>0.1.14</title>
      <link>https://pypi.org/project/lsynth/0.1.14/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 02:51:55 GMT</pubDate>
    </item>    <item>
      <title>0.1.13</title>
      <link>https://pypi.org/project/lsynth/0.1.13/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 02:45:26 GMT</pubDate>
    </item>    <item>
      <title>0.1.12</title>
      <link>https://pypi.org/project/lsynth/0.1.12/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 02:37:08 GMT</pubDate>
    </item>    <item>
      <title>0.1.11</title>
      <link>https://pypi.org/project/lsynth/0.1.11/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 02:09:54 GMT</pubDate>
    </item>    <item>
      <title>0.1.10</title>
      <link>https://pypi.org/project/lsynth/0.1.10/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 01:27:15 GMT</pubDate>
    </item>    <item>
      <title>0.1.9</title>
      <link>https://pypi.org/project/lsynth/0.1.9/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 01:25:45 GMT</pubDate>
    </item>    <item>
      <title>0.1.8</title>
      <link>https://pypi.org/project/lsynth/0.1.8/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sat, 13 Dec 2025 01:21:13 GMT</pubDate>
    </item>    <item>
      <title>0.1.7</title>
      <link>https://pypi.org/project/lsynth/0.1.7/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:42:58 GMT</pubDate>
    </item>    <item>
      <title>0.1.6</title>
      <link>https://pypi.org/project/lsynth/0.1.6/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:35:55 GMT</pubDate>
    </item>    <item>
      <title>0.1.5</title>
      <link>https://pypi.org/project/lsynth/0.1.5/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:21:08 GMT</pubDate>
    </item>    <item>
      <title>0.1.4</title>
      <link>https://pypi.org/project/lsynth/0.1.4/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:20:19 GMT</pubDate>
    </item>    <item>
      <title>0.1.3</title>
      <link>https://pypi.org/project/lsynth/0.1.3/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:12:48 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/lsynth/0.1.2/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:08:58 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/lsynth/0.1.1/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:07:05 GMT</pubDate>
    </item>    <item>
      <title>0.0.6</title>
      <link>https://pypi.org/project/lsynth/0.0.6/</link>
      <description>Evaluation of how good a synthetic dataset is compared to the original with presuppossing structural constraints</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 18:04:01 GMT</pubDate>
    </item>    <item>
      <title>0.1.0</title>
      <link>https://pypi.org/project/lsynth/0.1.0/</link>
      <description>MAP-alignment fidelity for synthetic tabular data</description>
<author>research@paraknowledge.ai</author>      <pubDate>Sun, 07 Dec 2025 17:49:50 GMT</pubDate>
    </item>  </channel>
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