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papersTODAY 04:00 UTC

CodeTS Generates Time Series from Text via Executable Code

A new arXiv paper introduces CodeTS, a method that turns natural-language descriptions into time series by generating and running executable code rather than sampling outputs directly. This design makes the resulting synthetic data verifiable and suited to scenarios where real observations are scarce or expensive to collect. The work appears in the cs.LG and cs.AI listings.

arXivCodeTSexecutable codemachine-learningsynthetic datatime series generation

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