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Symbolic Regression research benchmarks · SOTA2 Research

Symbolic Regression

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

SRBench black-box (test)

0.842R^2

71

May 27, 2026

Feynman benchmark

1Median Final Training Loss

60

Mar 31, 2026

3D Advection Equation (test)

0.123MSE

60

Feb 26, 2026

SRBench Strogatz (test)

0.995Mean Test R^2

59

May 27, 2026

SRBench Feynman (test)

99.7Mean Test R^2

57

May 27, 2026

SRBench 116 regression problems (test)

78Wins

55

Apr 1, 2026

E. coli growth LLM-SR Suite

0.001NMSE

44

Feb 27, 2026

2D Advection Equation (test)

0.138MSE

38

Feb 26, 2026

Jacobi-based SR problem

JBUA hybrid algorithm

0Error

34

Jun 4, 2026

Oscillator 1 (OOD)

0NMSE

32

May 19, 2026

Oscillation 1 LLM-SR Suite

0NMSE

30

Feb 27, 2026

LSR-Synth Material Science

0NMSE

23

Jun 4, 2026

LSR-Synth Physics

0NMSE

23

Jun 4, 2026

Stress–Strain (OOD)

0.032NMSE

23

Jun 4, 2026

Stress–Strain (ID)

0.006NMSE

23

Jun 4, 2026

Lung Cancer with Chemo & Radio (LC-CR) (test)

0.013MSE

22

May 29, 2026

63.57Overall Acc (Tol 0.01)

22

Feb 27, 2026

100Recall

22

Feb 26, 2026

Feynman Dataset ϵ = 0.0 (test)

0.996R^2

20

Feb 26, 2026

Strogatz Dataset ϵ = 0.0 (test)

0.995R^2

20

Feb 26, 2026

Feynman Dataset epsilon=0.1 (test)

0.996R2 Score

20

Feb 26, 2026

Strogatz Dataset epsilon=0.1 (test)

97.73R2

20

Feb 26, 2026

Feynman Dataset epsilon=0.01 (test)

0.997R2

20

Feb 26, 2026

Strogatz Dataset epsilon=0.01 (test)

0.994R2 Score

20

Feb 26, 2026

Feynman Dataset epsilon=0.001 (test)

99.62R2

20

Feb 26, 2026

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