NASPO_eval / README.md
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Initial NAS-PO dataset release: NASPO_eval
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metadata
dataset_info:
  features:
    - name: messages
      list:
        - name: content
          dtype: string
        - name: role
          dtype: string
    - name: images
      list: string
    - name: id
      dtype: string
  splits:
    - name: NASPO_MMK12
      num_examples: 2000
    - name: hiyouga_geometry3k
      num_examples: 601
    - name: AI4Math_MathVerse
      num_examples: 2180
    - name: AI4Math_MathVista
      num_examples: 1000
    - name: We_Math
      num_examples: 1740
    - name: MMMU_MMMU_Pro
      num_examples: 1730
    - name: AI4Math_MathVerse_vision_dependent
      num_examples: 1308
    - name: lscpku_LogicVista
      num_examples: 447
configs:
  - config_name: default
    data_files:
      - split: NASPO_MMK12
        path: data/NASPO_MMK12-*
      - split: hiyouga_geometry3k
        path: data/hiyouga_geometry3k-*
      - split: AI4Math_MathVerse
        path: data/AI4Math_MathVerse-*
      - split: AI4Math_MathVista
        path: data/AI4Math_MathVista-*
      - split: We_Math
        path: data/We_Math-*
      - split: MMMU_MMMU_Pro
        path: data/MMMU_MMMU_Pro-*
      - split: AI4Math_MathVerse_vision_dependent
        path: data/AI4Math_MathVerse_vision_dependent-*
      - split: lscpku_LogicVista
        path: data/lscpku_LogicVista-*
task_categories:
  - image-text-to-text
language:
  - en
library_name: datasets
tags:
  - multimodal
  - reasoning
  - evaluation

NAS-PO evaluation benchmark

This repository contains the eight evaluation configurations reported by NAS-PO. They are prepared from MMK12, Geometry3K, MathVerse, MathVista, We-Math, MMMU-Pro, and LogicVista.

The release contains eight Hugging Face dataset splits under data/ and one matching image ZIP for each split. The NAS-PO preprocessing command converts the selected splits to ShareGPT JSON and extracts the archives into its local data/images/ directory. Image references are portable paths relative to that materialized data root.

Usage

from datasets import load_dataset

mmk12 = load_dataset("ANke121/NASPO_eval", split="NASPO_MMK12")
assert len(mmk12) == 2000

The complete inference and Accuracy@8 workflow is provided by NASPO-Eval in the NAS-PO source repository.

Acknowledgements

The public PAPO release was used as a reference for organizing these files and the evaluation workflow. The individual datasets and benchmarks remain credited to their original creators and are subject to their respective licenses and terms.