kangaroo_dataset
type: Dataset
distribution: repo
distribution: parquet-files-for-config-default
record set: default_splits
record set: default
conforms to: http://mlcommons.org/croissant/1.1
description: German Kangaroo Benchmark This repository contains the finalized dataset artifact for the German Kangaroo benchmark, a longitudinal multimodal mathematical-reasoning benchmark derived from the German Mathematical Kangaroo competition corpus from 1998--2025. The authoritative dataset file is: full.parquet It contains 3,887 multiple-choice items across 140 exams and five grade buckets. Each row stores the question text, answer options, gold answer, point value, year, grade bucket… See the full description on the dataset page: https://huggingface.co/datasets/kangaroo-dataset-german/kangaroo_dataset.
alternate name: kangaroo-dataset-german/kangaroo_dataset
alternate name: German Kangaroo Benchmark
creator: kangaroo
keywords: question-answering
keywords: visual-question-answering
keywords: multiple-choice-qa
keywords: expert-generated
keywords: found
keywords: monolingual
keywords: original
keywords: German
keywords: cc-by-nc-4.0
keywords: 1K<n<10K
keywords: 🇺🇸 Region: US
keywords: mathematics
keywords: benchmark
keywords: multimodal
keywords: german
keywords: abstention
keywords: education
license: https://creativecommons.org/licenses/by-nc/4.0/
cite as: Anonymous authors. German Kangaroo Benchmark. NeurIPS 2026 submission artifact.
version: 1.0.0
data limitations: The dataset is German-only and may conflate mathematical reasoning with German-language competence. OCR and image extraction may introduce artifacts not present for original contest participants. Public historical contest materials may have appeared in model training data. The dataset is not recommended for grading students, making individual educational decisions, or replacing human exam calibration data.
data biases: The benchmark reflects the style, curriculum assumptions, and participation context of the German Mathematical Kangaroo competition. It may overrepresent visual-spatial contest problems and German school-mathematics conventions relative to broader mathematical reasoning or other student populations.
personal sensitive information: The dataset contains contest problems and aggregate metadata only. It does not contain personal information about participants.
data use cases: Intended uses include evaluating LLMs and vision-language models on German multimodal school mathematics, contest-faithful scoring, abstention behavior, and exam-level human-model comparison. Validity has been established only for benchmark-style model evaluation in this contest setting, not for human assessment or student-level decisions.
data social impact: The dataset can broaden multilingual and multimodal evaluation beyond English text-only benchmarks. A key risk is overinterpreting high model scores as evidence of human-like reasoning or stable exam-equating ability; the accompanying analysis explicitly cautions against that use.
has synthetic data: false
was generated by: The curation pipeline rasterizes question regions, applies OCR, preserves embedded visual content, and stores question and answer-option images as binary PNG payloads. The collection covers public German Mathematical Kangaroo competition materials from 1998--2025.

repo
type: FileObject
description: The Hugging Face git repository.
encoding format: git+https
sha256: https://github.com/mlcommons/croissant/issues/80

parquet-files-for-config-default
type: FileSet
contained in: repo
encoding format: application/x-parquet
includes: default/*/*.parquet

default_splits
type: RecordSet
data type: Split
key: split name
description: Splits for the default config.
field: split name
data:
  split name: train

default
type: RecordSet
description: kangaroo-dataset-german/kangaroo_dataset - 'default' subset
field: split
field: id
field: year
field: group
field: language
field: points
field: problem number
field: problem statement
field: answer
field: multimodal
field: sol A
field: sol B
field: sol C
field: sol D
field: sol E
field: question image
field: sol A image bin
field: sol B image bin
field: sol C image bin
field: sol D image bin
field: sol E image bin
field: associated images bin

split
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    file property: fullpath
  transform:
    regex: default/(?:partial-)?(train)/.+parquet$
references:
  field: split name

id
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: id

year
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: year

group
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: group

language
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: language

points
type: Field
data type: Int32
source:
  file set: parquet-files-for-config-default
  extract:
    column: points

problem number
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: problem_number

problem statement
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: problem_statement

answer
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: answer

multimodal
type: Field
data type: Boolean
source:
  file set: parquet-files-for-config-default
  extract:
    column: multimodal

sol A
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_A

sol B
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_B

sol C
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_C

sol D
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_D

sol E
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_E

question image
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: question_image

sol A image bin
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_A_image_bin

sol B image bin
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_B_image_bin

sol C image bin
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_C_image_bin

sol D image bin
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_D_image_bin

sol E image bin
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: sol_E_image_bin

associated images bin
type: Field
data type: Text
source:
  file set: parquet-files-for-config-default
  extract:
    column: associated_images_bin
is array: true
array shape: -1