All datasets / katebor

katebor/SciVQA

517 downloads in 30 days3 likesLast modified 3 Aug 2025View on Hugging Face

Permissive or share-alike

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at 7aa5cf2
Licence files: No licence file at the top level of the repositoryEvidence: file list at 7aa5cf2
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

visual-question-answering

Citation text from the card

@inproceedings{borisova-etal-2025-scivqa,
    title = "{S}ci{VQA} 2025: Overview of the First Scientific Visual Question Answering Shared Task",
    author = "Borisova, Ekaterina  and
      Rauscher, Nikolas  and
      Rehm, Georg",
    editor = "Ghosal, Tirthankar  and
      Mayr, Philipp  and
      Singh, Amanpreet  and
      Naik, Aakanksha  and
      Rehm, Georg  and
      Freitag, Dayne  and
      Li, Dan  and
      Schimmler, Sonja  and
      De Waard, Anita",
    booktitle = "Proceedings of the Fifth Workshop on Scholarly Document Processing (SDP 2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.sdp-1.18/",
    pages = "182--210",
    ISBN = "979-8-89176-265-7",
    abstract = "This paper provides an overview of the First Scientific Visual Question Answering (SciVQA) shared task conducted as part of the Fifth Scholarly Document Processing workshop (SDP 2025). SciVQA aims to explore the capabilities of current multimodal large language models (MLLMs) in reasoning over figures from scholarly publications for question answering (QA). The main focus of the challenge is on closed-ended visual and non-visual QA pairs. We developed the novel SciVQA benchmark comprising 3,000 images of figures and a total of 21,000 QA pairs. The shared task received seven submissions, with the best performing system achieving an average F1 score of approx. 0.86 acros

All datasets marked Permissive or share-alike | JSON

The same facts for your agent

A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.

dataset_licence({ "id": "katebor/SciVQA" })
signal: "permissive"
stated_licence: "mit"
sources: 0