SymbolicRegressionQA

SymbolicRegressionQA (SRQA) is a multiple-choice visual question answering dataset introduced in Bayesian Adaptation Gym (UAI 2026). Each question shows a plot of a symbolic expression and asks which of four candidate formulas describes the relationship between the variables.

Splits

Split	Examples
train	10,000
validation	1,000
test	1,000

Fields

Field	Type	Description
image	Image	224x224 grayscale plot of the ground truth expression
choices	list[str]	Four candidate formulas, in the order they are presented
label	str	Letter of the correct choice, one of A, B, C, D
sympy_reprs	list[str]	SymPy representation of each of the four choices
degrees	list[int]	Polynomial degree of each of the four choices
question_id	int	Unique identifier within the split

The correct answer is close to uniform over the four letters in every split.

Usage

from datasets import load_dataset

data = load_dataset("csamplawski/SymbolicRegressionQA", split="test")

The prompt used in the BAG experiments is built from choices as follows:

For the provided image of a plot, which of following formulas best describes the relationship between the variables? Output the letter of your choice only.
Choices:
A) <choices[0]>
B) <choices[1]>
C) <choices[2]>
D) <choices[3]>

See bayesadapt/datasets/srqa.py in BayesAdapt for the loader used in the paper.

Citation

@misc{samplawski2026bayesianadaptationgymbenchmark,
      title={Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models}, 
      author={Colin Samplawski and Ramneet Kaur and Manoj Acharya and Anirban Roy and Adam D. Cobb},
      year={2026},
      eprint={2606.22188},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2606.22188}, 
}