Provenance Tracking in AI Compilers through the Lens of Coalgebra
AI compilers aggressively rewrite computation graphs through normalization, lowering, and optimization, making it difficult to track the provenance of tensors and operators across compilation. Reliable provenance is essential for attaching platform-specific postprocessing, debugging compiler behavior, and validating transformations, yet existing solutions are either invasive or ad hoc under non-injective graph rewrites. We present a lightweight, generative approach to provenance tracking based on observational semantics. Instead of propagating identifiers through compiler passes, we observe graph transformations and reason about provenance in terms of observable computational actions. We ...
| Authors | Zilu Tian, Liying Liu |
|---|---|
| Primary category | cs.DB |
| Published | 9 June 2026 |
| Last updated at source | 9 June 2026 |
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