datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
upper-hessenberg-polynomialspolynomial-root-finding-dataset
Polynomial Root Finding Dataset (With Out-of-Distribution Gaps)
Dataset Description
This dataset provides a massive, synthetically generated collection of polynomial equations (ranging from degrees 1 to 4) alongside their real roots. It is explicitly designed for benchmarking Machine Learning models (such as Transformers or Mixture Density Networks) on mathematical reasoning, continuous numerical embeddings, and rigorous Out-of-Distribution (OoD) generalization.
The… See the full description on the dataset page: https://huggingface.co/datasets/karankhatavkar/polynomial-root-finding-dataset.lab1_EDAN20polynomial-fit-dataunstructured-characteristic-polynomialsschubert_polynomial_structure_constants_4
A Combinatorial Interpretation of Schubert Polynomial Structure Constants
Schubert polynomials [1,2,3] are a family of polynomials indexed by permutations of SnS_nSn.
Developed to study the cohomology ring of the flag variety, they have deep connections to
algebraic geometry, Lie theory, and representation theory. Despite their geometric origins,
Schubert polynomials can be described combinatorially [4,5], making them a well-studied object
in algebraic combinatorics. An… See the full description on the dataset page: https://huggingface.co/datasets/ACDRepo/schubert_polynomial_structure_constants_4.schubert_polynomial_structure_constants_6
A Combinatorial Interpretation of Schubert Polynomial Structure Constants
Schubert polynomials [1,2,3] are a family of polynomials indexed by permutations of SnS_nSn.
Developed to study the cohomology ring of the flag variety, they have deep connections to
algebraic geometry, Lie theory, and representation theory. Despite their geometric origins,
Schubert polynomials can be described combinatorially [4,5], making them a well-studied object
in algebraic combinatorics. An… See the full description on the dataset page: https://huggingface.co/datasets/ACDRepo/schubert_polynomial_structure_constants_6.coefficients_of_kl_polynomials_7
The Coefficients of Kazhdan-Lusztig Polynomials for Permutations of Size 7
Kazhdan-Lusztig (KL) polynomials are polynomials in a variable qqq and
with integer coefficients that (for our purposes) are indexed by a pair of permutations [1].
We will write the KL polynomial associated with permutations σ\sigmaσ and ν\nuν as Pσ,ν(q)P_{\sigma,\nu}(q)Pσ,ν(q). For example, the KL polynomial associated with permutations σ=1 4 3 2 7 6 5 10 9 8 11\sigma = 1 \; 4 \; 3 \; 2 \; 7… See the full description on the dataset page: https://huggingface.co/datasets/ACDRepo/coefficients_of_kl_polynomials_7.antiderivative_polynomial
Antiderivative Polynomial Dataset
Dataset Summary
The Antiderivative Polynomial dataset is a collection of polynomial functions and their antiderivatives. The dataset is generated using polynomial functions and their antiderivatives.
Plot from the dataset:
Dataset Structure
The dataset is structured as follows.
Subsets
The dataset is divided into two subsets:
default: the default dataset.
aligned: the X values are aligned for all functions.… See the full description on the dataset page: https://huggingface.co/datasets/ajthor/antiderivative_polynomial.ptdbench-reward-design-reward-polynomial-factorization-035-dataset
PTDBench dataset snapshot: reward_polynomial_factorization_035
This repository stores the immutable runtime dataset snapshot for one
materialized PTDBench task. It intentionally excludes model weights and
training checkpoints.
PTDBench family: reward_design
Source evaluation metric: eval/HELD-OUT_ENVIRONMENTS_128
Provenance: RLVE repository snapshot under its MIT license; bundled upstream benchmark notices remain applicable.
License: MIT
The artifact manifest records every… See the full description on the dataset page: https://huggingface.co/datasets/LIF1014/ptdbench-reward-design-reward-polynomial-factorization-035-dataset.polynomial
Polynomial Dataset
Dataset Summary
The Polynomial dataset is a collection of polynomial functions.
Plot from the dataset:
Dataset Structure
The dataset is structured as follows.
Subsets
The dataset has one subset:
default: the default dataset.
Splits
The dataset is divided into two splits:
train: the training split, consisting of 10,000 rows.
test: the test split, consisting of 1,000 rows.
Columns
Each row in the dataset… See the full description on the dataset page: https://huggingface.co/datasets/ajthor/polynomial.derivative_polynomial
Derivative Polynomial Dataset
Dataset Summary
The Derivative Polynomial dataset is a collection of polynomial functions and their
derivatives. The dataset is generated using polynomial functions and their derivatives.
Plot from the dataset:
Dataset Structure
The dataset is structured as follows.
Subsets
The dataset is divided into two subsets:
default: the default dataset.
aligned: the X values are aligned for all functions.
Splits
The… See the full description on the dataset page: https://huggingface.co/datasets/ajthor/derivative_polynomial.schubert_polynomial_structure_constants_5
A Combinatorial Interpretation of Schubert Polynomial Structure Constants
Schubert polynomials [1,2,3] are a family of polynomials indexed by permutations of SnS_nSn.
Developed to study the cohomology ring of the flag variety, they have deep connections to
algebraic geometry, Lie theory, and representation theory. Despite their geometric origins,
Schubert polynomials can be described combinatorially [4,5], making them a well-studied object
in algebraic combinatorics. An… See the full description on the dataset page: https://huggingface.co/datasets/ACDRepo/schubert_polynomial_structure_constants_5.coefficients_of_kl_polynomials_6
The Coefficients of Kazhdan-Lusztig Polynomials for Permutations of Size 6
Kazhdan-Lusztig (KL) polynomials are polynomials in a variable qqq and
with integer coefficients that (for our purposes) are indexed by a pair of permutations [1].
We will write the KL polynomial associated with permutations σ\sigmaσ and ν\nuν as Pσ,ν(q)P_{\sigma,\nu}(q)Pσ,ν(q). For example, the KL polynomial associated with permutations σ=1 4 3 2 7 6 5 10 9 8 11\sigma = 1 \; 4 \; 3 \; 2 \; 7… See the full description on the dataset page: https://huggingface.co/datasets/ACDRepo/coefficients_of_kl_polynomials_6.polynomial-equations-1to4-degreemath_algebra_polynomial_roots_test_inpolynomial_multiplicationmath_algebra_polynomial_roots_7B_trainmath_algebra_polynomial_roots_7B_test_inmath_algebra_polynomial_roots_7B_test_outcoefficients_of_kl_polynomials_5
The Coefficients of Kazhdan-Lusztig Polynomials for Permutations of Size 5
Kazhdan-Lusztig (KL) polynomials are polynomials in a variable qqq and
with integer coefficients that (for our purposes) are indexed by a pair of permutations [1].
We will write the KL polynomial associated with permutations σ\sigmaσ and ν\nuν as Pσ,ν(q)P_{\sigma,\nu}(q)Pσ,ν(q). For example, the KL polynomial associated with permutations σ=1 4 3 2 7 6 5 10 9 8 11\sigma = 1 \; 4 \; 3 \; 2 \; 7… See the full description on the dataset page: https://huggingface.co/datasets/ACDRepo/coefficients_of_kl_polynomials_5.polynomial-propertiesomega-combined-split-algebra_polynomial_rootspolynomial_problemsunstructured-minimal-polynomialsmath_comp_polynomial_gcdpolynomial-equations-unique-1to4-degreepolynomial_root_analysisPolynomials_Coefficientpolynomial_equations