repo
The Hugging Face git repository.
git+https
application/x-parquet
default/*/*.parquet
default_splits
Splits for the default config.
train
kangaroo-dataset-german/kangaroo_dataset - 'default' subset
fullpath
default/(?:partial-)?(train)/.+parquet$
year
group
language
points
problem_number
problem_statement
answer
multimodal
sol_A
sol_B
sol_C
sol_D
sol_E
question_image
sol_A_image_bin
sol_B_image_bin
sol_C_image_bin
sol_D_image_bin
sol_E_image_bin
associated_images_bin
kangaroo_dataset
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.
kangaroo-dataset-german/kangaroo_dataset
German Kangaroo Benchmark
kangaroo
question-answering
visual-question-answering
multiple-choice-qa
expert-generated
found
monolingual
original
German
cc-by-nc-4.0
1K<n<10K
🇺🇸 Region: US
mathematics
benchmark
german
abstention
education
Anonymous authors. German Kangaroo Benchmark. NeurIPS 2026 submission artifact.
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.
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.
The dataset contains contest problems and aggregate metadata only. It does not contain personal information about participants.
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.
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.
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.