Add task for SEGData (German VQA) - #3963
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This commit adds a description of the paper, a incomplete citation and a description of the correct usage of the task.
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Aug 14, 2026
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Hi! Thanks for the PR. Made a couple of modifications, just confirming if you're happy with them. The main one is that previously there wasn't any whitespace normalization to the model responses so <space>A would have been wrong. Added a filter to extract the letter.
Also thought 5 tokens would be a bit low, so increased to 16 but it shouldn't make that much a difference. Feel free to revert.
| Beschreibung: {{ description }} | ||
| Frage: {{ text }} | ||
| Antwortmöglichkeiten: | ||
| {{ answers | join("\n") }} |
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as answers was a python list, this stringifies with newline delimitation.
| generation_kwargs: | ||
| until: | ||
| - "\n\n" | ||
| max_gen_toks: 16 |
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though 5 would be a bit low
| # `gold_answer` is always a single letter, so take the first standalone | ||
| # letter in the response. Case is normalized by the metric below. | ||
| - function: regex | ||
| regex_pattern: "\\b([A-Za-z])\\b" |
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this normalizes leading whitespace such as A.
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This adds a task for mainly German multiple-choice Visual Question Answering data that covers divers domains.
The original data is designed by the Institut zur Qualitätsentwicklung im Bildungswesen to test German school children in classes 3, 8 and 12. It is freely accessible at their website.
Details of the dataset can be found here: https://huggingface.co/datasets/DFKI-SLT/SEGData
A link to the abstract and the full citation will be added as soon as their are available.
The dataset was originally started as a pull request here, but had to be renamed afterwards