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Datasets:
mbhosale
/
CRAFT-MAGMaR

Tasks:
Visual Question Answering
Video-Text-to-Text
Languages:
English
Burmese
Nepali
ArXiv:
Tags:
video-qa
multi-video
news
magmar
craft
retrieval-augmented-generation
License:
Dataset card Files
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Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
2025_Myanmar_Earthquake: list<item: string>
  child 0, item: string
2025_Canadian_Federal_Election: list<item: string>
  child 0, item: string
Blue_Ghost_Mission_1: list<item: string>
  child 0, item: string
Liberation_Day_Tariffs: list<item: string>
  child 0, item: string
query_type: string
query_id: string
title: string
query: string
language: string
background: string
persona_title: string
to
{'query_id': Value('string'), 'query_type': Value('string'), 'language': Value('string'), 'title': Value('string'), 'persona_title': Value('string'), 'background': Value('string'), 'query': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              2025_Myanmar_Earthquake: list<item: string>
                child 0, item: string
              2025_Canadian_Federal_Election: list<item: string>
                child 0, item: string
              Blue_Ghost_Mission_1: list<item: string>
                child 0, item: string
              Liberation_Day_Tariffs: list<item: string>
                child 0, item: string
              query_type: string
              query_id: string
              title: string
              query: string
              language: string
              background: string
              persona_title: string
              to
              {'query_id': Value('string'), 'query_type': Value('string'), 'language': Value('string'), 'title': Value('string'), 'persona_title': Value('string'), 'background': Value('string'), 'query': Value('string')}
              because column names don't match

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CRAFT-MAGMaR

MAGMaR-2026 plus the CRAFT-specific artefacts our pipeline needs end-to-end. Sources: the MAGMaR-2026 test release from akhilvssg/magmar-2026-test-asr-embeddings

  • content produced by the CRAFT pipeline (chunking, multilingual ASR, adaptive keyframe selection).

Contents

Path What it is
en/ All MAGMaR videos in one flat directory: 90 original mp4s plus 72 CRAFT-produced <video_id>__chunkNNN.mp4 splits. Point VIDEO_ROOT here.
asr/ Per-video transcripts (<video_id>.json) from Qwen3-ASR-1.7B with omniASR-LLM-7B fallback for Burmese / Nepali. Schema: {video_id, asr_model, language, text, text_en, needs_fallback, no_audio, asr_loop_detected}.
aks/outscores/ DKS / AKS keyframe scores per (query, video) pair (CLIP-based).
aks/selected_frames/ Selected keyframe indices per (query, video) pair, top-64.
MAGMaR2026_queries.jsonl Official MAGMaR-2026 test queries (19 personas).
MAGMaR2026_queries_dev.jsonl Official MAGMaR-2026 dev queries (8 personas).
topic_video_mapping_v2.json Test split: topic / event -> list of (chunked) video IDs.
topic_video_mapping_dev_v2.json Dev split: topic / event -> list of (chunked) video IDs.
video_chunk_map.json chunk_id -> {video_id, start, end}, used to remap chunked citations back to parent video IDs at output-formatting time.

This bundle does not redistribute the MAGMaR-2026 ground-truth labels. Score your runs with the MIRAGE judge against the official ground truth obtained directly from the MAGMaR workshop.

Usage with CRAFT 

# Download
hf download mbhosale/CRAFT-MAGMaR --repo-type dataset \
    --local-dir /path/to/MAGMaR2026_test

# Run CRAFT against it (no chunking needed, ships pre-chunked)
git clone https://github.com/bhosalems/CRAFT.git && cd CRAFT
conda create -n craft python=3.13 -y && conda activate craft
pip install -r requirements.txt

SKIP_CHUNK=1 \
VIDEO_ROOT=/path/to/MAGMaR2026_test \
ASR_DIR=/path/to/MAGMaR2026_test/asr \
PARALLEL_QUERIES=8 PARALLEL_STEP15=8 PARALLEL_STEP5=8 \
    bash run_query.sh outputs/craft_magmar_main

See the CRAFT repository for the full pipeline (Stage 1b VLM extraction, hybrid critic loop, UNLI calibration, higher-level inference, report assembly) and the MIRAGE evaluator setup.

Licensing

The base videos and queries come from the MAGMaR-2026 test release at akhilvssg/magmar-2026-test-asr-embeddings. Please honour that dataset's license for any downstream redistribution. CRAFT-produced artefacts (chunks, ASR cache, AKS outputs) are released under the same terms.

Citation 

@article{bhosale2026craft,
  title={CRAFT: Critic-Refined Adaptive Key-Frame Targeting for Multimodal Video Question Answering},
  author={Bhosale, Mahesh and Wasi, Abdul and Trivedi, Vishvesh and Yan, Pengyu and Gorugantu, Akhil and Doermann, David},
  journal={arXiv preprint arXiv:2605.19075},
  year={2026}
}
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Paper for mbhosale/CRAFT-MAGMaR