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195
Cross-industry multimodal multiple-choice VQA benchmark (21 sectors; eval-only). Category B, task T-B3, in the unified Smart-Manufacturing SFT schema.
The repository name is an internal task code. See Provenance below for the underlying dataset.
Records
1,050 records (test=1050).
Unified SFT schema
| field | type | meaning |
|---|---|---|
query |
str | the question / instruction (model input) |
image |
Image | the input image (bytes embedded) |
annot |
str | the answer — for this dataset: the bare gold option letter (A-E; E is a 'cannot recognize' reject option), exactly the benchmark's answer. The 5 options are given in the query and in metadata.choices; the option text, the industrial category, and the parallel Chinese question/choices/answer are in metadata — see Task & split below |
reasoning |
null | no native CoT in these datasets |
cate |
"B" | SFT category |
task |
"T-xx" | unified task id |
metadata |
str (JSON) | split, provenance, image_path, image_sha256 (dedup key) |
mask |
Image | null | (T-B1/T-B2 only) the pixel ground-truth mask, bytes embedded |
masks |
list[Image] | (D21 only) multi-region masks |
Task & split
What this is. MME-Industry (arXiv 2501.16688) — a cross-industry multimodal evaluation benchmark for MLLMs: 1,050 expert-authored multiple-choice questions over 21 industrial sectors (50 each, e.g. power, steel, chemical, textile, medical). Questions are deliberately non-OCR (they require domain reasoning, not text reading). It is an eval-only benchmark scored by multiple-choice accuracy.
Query & answer (this repo's SFT task). query = the question followed by the 5 options (A)…(E) and the
instruction to answer with a single letter; annot = the bare gold option letter (A–E). Option E is a
No corresponding features in the picture reject option. The option text, the industrial category, and the
full set of options are in metadata.
Bilingual. The benchmark ships parallel English and Chinese versions (index-aligned). English is
authoritative for query/annot; the Chinese question / choices / category / answer are preserved in
metadata (question_zh, choice_zh, category_zh, answer_zh). The two languages agree on the answer for
1,049 / 1,050 items; where they differ, the English answer is used.
No mask. This is VQA, not localization — there is no mask column.
Split. Single test split (1,050) — it is an evaluation benchmark, not a training set.
Provenance
Underlying dataset: MME-Industry. Upstream license: Apache-2.0 (this card is license: other; respect the upstream terms). Converted read-only from the raw source into the unified schema; conversion script: 195/convert_d95.py, published with publish/push_to_hf.py, both in AI4Manufacturing/forge_model.
Overlap / de-duplication (§8)
Evaluation benchmark (single test split); expert-authored, non-OCR — no image overlap with the other datasets. Each record carries metadata.image_sha256 so overlapping images can be kept entirely on one side of a train/eval split.
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