Machine Learning · 2026-11-11

The Shape of a Program: Path Signatures for Trace-to-Program Induction

arXiv:2611.13005v1 Announce Type: new Abstract: Synthesizing programs from execution traces is a fundamental challenge in algorithmic interpretability and the reverse engineering of complex systems. We bring a rough-path-theoretic perspective to program induction, treating execution traces as high-dimensional rough paths and encoding them with the path signature transform, a tool from stochastic analysis whose…

SHARE THIS ARTICLE LinkedIn X Facebook

arXiv:2611.13005v1 Announce Type: new Abstract: Synthesizing programs from execution traces is a fundamental challenge in algorithmic interpretability and the reverse engineering of complex systems. We bring a rough-path-theoretic perspective to program induction, treating execution traces as high-dimensional rough paths and encoding them with the path signature transform, a tool from stochastic analysis whose expectation provably characterizes the distribution of traces a program induces. On three program-induction domains, Karel, List, and RASP, our log-signature trace encoder outperforms LSTM, Transformer, and Fourier baselines in almost every setting, with its largest margins when training data is scarce.

Source and attribution

Original source: arXiv ML ↗

This is an attributed editorial digest. For the complete study and original reporting, follow the source link.

Reader feedback

0 likes · 0 dislikes

Sign in to like or dislike this research.

SHARE THIS ARTICLE LinkedIn X Facebook
← Back to research archive