Initial anonymized dataset release

.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.avro filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
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-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
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LICENSE

@@ -0,0 +1,10 @@
+Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
+
+This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International License.
+
+License text: https://creativecommons.org/licenses/by-nc/4.0/legalcode
+Human-readable summary: https://creativecommons.org/licenses/by-nc/4.0/
+
+You are free to share and adapt the dataset for non-commercial purposes, provided that you give appropriate credit, provide a link to the license, and indicate if changes were made.
+
+The benchmark is derived from German Mathematical Kangaroo competition materials. Users should attribute both this dataset and the original German Mathematical Kangaroo source materials. Commercial use requires additional permission.

README.md

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+---
+annotations_creators:
+- expert-generated
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: full.parquet
+language:
+- de
+language_creators:
+- found
+license:
+- cc-by-nc-4.0
+multilinguality:
+- monolingual
+pretty_name: German Kangaroo Benchmark
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- question-answering
+- visual-question-answering
+task_ids:
+- multiple-choice-qa
+- visual-question-answering
+tags:
+- mathematics
+- benchmark
+- multimodal
+- german
+- abstention
+- education
+---
+
+# 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:
+
+```text
+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, modality flag, and embedded image fields for question and option images.
+
+## Intended Use
+
+The dataset is intended for evaluating language and vision-language models on German school-mathematics problems under contest-faithful multiple-choice scoring. It supports analysis of text-only reasoning, multimodal reasoning, answer-selection behavior under negative marking, and comparisons between model performance and official aggregate human contest statistics.
+
+The dataset should not be used to infer that a model reasons like a human student, to grade students, or to replace human reference data for exam calibration. The accompanying paper finds that current LLM scores do not provide stable reference anchors for human exam difficulty.
+
+## Files
+
+| File | Description |
+| --- | --- |
+| `full.parquet` | Final corrected benchmark dataset used for the paper. |
+| `schema.md` | Column-level schema description. |
+| `evaluation_protocol.md` | Summary of the contest-faithful evaluation protocol. |
+| `croissant.jsonld` | Croissant metadata with responsible-AI fields for NeurIPS submission. |
+
+## Dataset Structure
+
+The Parquet file has 3,887 rows and 21 columns:
+
+```text
+id
+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
+```
+
+Image columns store PNG bytes or null values. `associated_images_bin` stores a list of additional embedded image payloads where applicable.
+
+## Scoring
+
+The benchmark follows the original contest scoring structure. Items are worth 3, 4, or 5 points. A correct answer receives the full item value, an incorrect answer loses one quarter of the item value, and abstention receives zero points. Normalized exam scores are reported as percent of the maximum achievable score for that exam.
+
+## Source and Provenance
+
+The benchmark is curated from public German Mathematical Kangaroo competition materials covering 1998--2025. The dataset construction pipeline rasterizes question regions, applies OCR, preserves embedded visual content, and stores question and option images directly in the Parquet file.
+
+## Limitations
+
+The dataset is German-only, so model performance may reflect both mathematical reasoning and German-language competence. The curation process uses OCR and image extraction, which may introduce artifacts not present for original human contest participants. Older contest materials may have appeared in model training data. Official human reference data is aggregate rather than item-level, so the benchmark supports exam-level comparison but not item-response modeling against human responses.
+
+## License
+
+This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0): https://creativecommons.org/licenses/by-nc/4.0/
+
+The benchmark is derived from German Mathematical Kangaroo competition materials. Users must provide appropriate attribution to the dataset authors and the original German Mathematical Kangaroo source materials, may use the dataset for non-commercial research and evaluation, and may not use it for commercial purposes without additional permission.
+
+## Citation
+
+Citation information will be added after the associated paper is finalized.

croissant.jsonld

@@ -0,0 +1,444 @@
+{
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+    "@language": "en",
+    "@vocab": "https://schema.org/",
+    "arrayShape": "cr:arrayShape",
+    "citeAs": "cr:citeAs",
+    "column": "cr:column",
+    "conformsTo": "dct:conformsTo",
+    "containedIn": "cr:containedIn",
+    "cr": "http://mlcommons.org/croissant/",
+    "data": {
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+      "@type": "@json"
+    },
+    "dataBiases": "cr:dataBiases",
+    "dataCollection": "cr:dataCollection",
+    "dataType": {
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+    "dct": "http://purl.org/dc/terms/",
+    "extract": "cr:extract",
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+    "isLiveDataset": "cr:isLiveDataset",
+    "jsonPath": "cr:jsonPath",
+    "key": "cr:key",
+    "md5": "cr:md5",
+    "parentField": "cr:parentField",
+    "path": "cr:path",
+    "personalSensitiveInformation": "cr:personalSensitiveInformation",
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+    "regex": "cr:regex",
+    "repeated": "cr:repeated",
+    "replace": "cr:replace",
+    "sc": "https://schema.org/",
+    "separator": "cr:separator",
+    "source": "cr:source",
+    "subField": "cr:subField",
+    "transform": "cr:transform",
+    "rai": "http://mlcommons.org/croissant/RAI/",
+    "prov": "http://www.w3.org/ns/prov#"
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+      "encodingFormat": "git+https",
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+      "description": "Splits for the default config.",
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+      "@id": "default",
+      "description": "kangaroo-dataset-german/kangaroo_dataset - 'default' subset",
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+          "dataType": "sc:Text",
+          "source": {
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+            },
+            "extract": {
+              "column": "id"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/year",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "year"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/group",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "group"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/language",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "language"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/points",
+          "dataType": "cr:Int32",
+          "source": {
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+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "points"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/problem_number",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "problem_number"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/problem_statement",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "problem_statement"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/answer",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "answer"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/multimodal",
+          "dataType": "sc:Boolean",
+          "source": {
+            "fileSet": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_A",
+          "dataType": "sc:Text",
+          "source": {
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+            },
+            "extract": {
+              "column": "sol_A"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_B",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_B"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_C",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_C"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_D",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_D"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_E",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_E"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/question_image",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "question_image"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_A_image_bin",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_B_image_bin",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_B_image_bin"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_C_image_bin",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
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+            },
+            "extract": {
+              "column": "sol_C_image_bin"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_D_image_bin",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_D_image_bin"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/sol_E_image_bin",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "sol_E_image_bin"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "default/associated_images_bin",
+          "dataType": "sc:Text",
+          "source": {
+            "fileSet": {
+              "@id": "parquet-files-for-config-default"
+            },
+            "extract": {
+              "column": "associated_images_bin"
+            }
+          },
+          "isArray": true,
+          "arrayShape": "-1"
+        }
+      ]
+    }
+  ],
+  "conformsTo": "http://mlcommons.org/croissant/1.1",
+  "name": "kangaroo_dataset",
+  "description": "\n\t\n\t\t\n\t\tGerman Kangaroo Benchmark\n\t\n\nThis 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.\nThe authoritative dataset file is:\nfull.parquet\n\nIt 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.",
+  "alternateName": [
+    "kangaroo-dataset-german/kangaroo_dataset",
+    "German Kangaroo Benchmark"
+  ],
+  "creator": {
+    "@type": "Person",
+    "name": "kangaroo",
+    "url": "https://huggingface.co/kangaroo-dataset-german"
+  },
+  "keywords": [
+    "question-answering",
+    "visual-question-answering",
+    "multiple-choice-qa",
+    "visual-question-answering",
+    "expert-generated",
+    "found",
+    "monolingual",
+    "original",
+    "German",
+    "cc-by-nc-4.0",
+    "1K<n<10K",
+    "🇺🇸 Region: US",
+    "mathematics",
+    "benchmark",
+    "multimodal",
+    "german",
+    "abstention",
+    "education"
+  ],
+  "license": "https://creativecommons.org/licenses/by-nc/4.0/",
+  "url": "https://huggingface.co/datasets/kangaroo-dataset-german/kangaroo_dataset",
+  "citeAs": "Anonymous authors. German Kangaroo Benchmark. NeurIPS 2026 submission artifact.",
+  "version": "1.0.0",
+  "rai:dataLimitations": "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.",
+  "rai:dataBiases": "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.",
+  "rai:personalSensitiveInformation": "The dataset contains contest problems and aggregate metadata only. It does not contain personal information about participants.",
+  "rai:dataUseCases": "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.",
+  "rai:dataSocialImpact": "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.",
+  "rai:hasSyntheticData": false,
+  "prov:wasDerivedFrom": {
+    "@id": "https://www.mathe-kaenguru.de/"
+  },
+  "prov:wasGeneratedBy": "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."
+}

evaluation_protocol.md

@@ -0,0 +1,28 @@
+# Evaluation Protocol
+
+The benchmark is designed for single-turn exam-mode evaluation.
+
+Each item is presented once with:
+
+- German problem text,
+- five answer choices `A`--`E`,
+- any question image,
+- any image-based answer options.
+
+The model must return either one final answer letter or an explicit abstention token such as `Declined`.
+
+Scoring follows the original contest rules:
+
+- correct answer: `+points`,
+- wrong answer: `-points / 4`,
+- abstention: `0`.
+
+Accuracy treats abstentions as incorrect so that solving performance and abstention policy can be analyzed separately.
+
+Exam-level results should report both raw contest points and normalized percent maximum score:
+
+```text
+percent_max = total_points / maximum_possible_points * 100
+```
+
+Evaluation should avoid tool use, retrieval, multi-turn correction, or item revisiting unless explicitly reported as a separate protocol.

full.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c5c50053a8fdcad9f9fe6f651c51eb475c9f9036392f82e22b89284bb7460d4
+size 482715171

schema.md

@@ -0,0 +1,29 @@
+# Schema
+
+The authoritative dataset file is `full.parquet`. It contains 3,887 rows and 21 columns.
+
+| Column | Type | Description |
+| --- | --- | --- |
+| `id` | string | Stable item identifier. |
+| `year` | string | Competition year. |
+| `group` | string | Grade bucket: `3-4`, `5-6`, `7-8`, `9-10`, or `11-13`. |
+| `language` | string | Item language; currently `de`. |
+| `points` | int32 | Official item value: 3, 4, or 5. |
+| `problem_number` | string | Problem number within the exam. |
+| `problem_statement` | string | OCR-corrected problem statement text. |
+| `answer` | string | Gold multiple-choice answer label: `A`, `B`, `C`, `D`, or `E`. |
+| `multimodal` | bool | Whether the item contains a question image or image-based answer option. |
+| `sol_A` | string/null | Text for answer option A when available. |
+| `sol_B` | string/null | Text for answer option B when available. |
+| `sol_C` | string/null | Text for answer option C when available. |
+| `sol_D` | string/null | Text for answer option D when available. |
+| `sol_E` | string/null | Text for answer option E when available. |
+| `question_image` | bytes/null | PNG bytes for the question crop or visual stem. |
+| `sol_A_image_bin` | bytes/null | PNG bytes for graphical answer option A. |
+| `sol_B_image_bin` | bytes/null | PNG bytes for graphical answer option B. |
+| `sol_C_image_bin` | bytes/null | PNG bytes for graphical answer option C. |
+| `sol_D_image_bin` | bytes/null | PNG bytes for graphical answer option D. |
+| `sol_E_image_bin` | bytes/null | PNG bytes for graphical answer option E. |
+| `associated_images_bin` | list | Additional associated PNG image payloads where applicable. |
+
+Image fields are stored directly as binary payloads. Text answer fields may be null when the corresponding answer option is graphical.