A complex-weight extension to the Equation Learner enables stable recovery of symbolic expressions containing real-domain poles and unconstrained use of singular operators such as division and logarithm.
Journal of Data-centric Machine Learning Research , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
MIRA-Math introduces a 2,310-instance benchmark isolating the ability of LLMs to request a single missing atomic fact needed to solve an underdetermined mathematical problem and then integrate it into an exact answer.
citing papers explorer
-
Complex Equation Learner: Rational Symbolic Regression with Gradient Descent in Complex Domain
A complex-weight extension to the Equation Learner enables stable recovery of symbolic expressions containing real-domain poles and unconstrained use of singular operators such as division and logarithm.
-
MIRA-Math: A Benchmark for Minimal Information Requesting and Mathematical Reasoning
MIRA-Math introduces a 2,310-instance benchmark isolating the ability of LLMs to request a single missing atomic fact needed to solve an underdetermined mathematical problem and then integrate it into an exact answer.