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20212026
most citedbabble: Learning Better Abstractions with E-Graphs and Anti-Unification

39 citations · 43 across the 6 of their papers we have counts for

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cs.PL2026

Numerical Superoptimization for Library Learning

Jonas Regehr, Mitch Briles, Zachary Tatlock +1

Numerical software depends on fast, accurate implementations of mathematical primitives like sin, exp, and log. Modern superoptimizers can optimize floating-point kernels against a…

cs.PL20241 cited

Scaling Program Synthesis Based Technology Mapping with Equality Saturation

Gus Henry Smith, Colin Knizek, Daniel Petrisko +5

State-of-the-art hardware compilers for FPGAs often fail to find efficient mappings of high-level designs to low-level primitives, especially complex programmable primitives like d…

cs.PL20233 cited

Better Together: Unifying Datalog and Equality Saturation

Yihong Zhang, Yisu Remy Wang, Oliver Flatt +5

We present egglog, a fixpoint reasoning system that unifies Datalog and equality saturation (EqSat). Like Datalog, it supports efficient incremental execution, cooperating analyses…

cs.PL202239 cited

babble: Learning Better Abstractions with E-Graphs and Anti-Unification

David Cao, Rose Kunkel, Chandrakana Nandi +3

Library learning compresses a given corpus of programs by extracting common structure from the corpus into reusable library functions. Prior work on library learning suffers from t…

cs.PL2021

Rewrite Rule Inference Using Equality Saturation

Chandrakana Nandi, Max Willsey, Amy Zhu +6

Many compilers, synthesizers, and theorem provers rely on rewrite rules to simplify expressions or prove equivalences. Developing rewrite rules can be difficult: rules may be subtl…