license: cc-by-nc-4.0
task_categories:
- audio-classification
language:
- en
pretty_name: MIA_LALM
MIA_LALM
Audio datasets for Membership Inference Attacks against Large Audio Language Models (arXiv, code).
The audio is distributed as one zstd-compressed tar per dataset family. A few large archives download far faster than ~90k individual WAV files (no per-file overhead, no HTTP 429), and each extracts to the exact layout the attack runners expect.
Download
With the code repository cloned,
download each family into MIA_on_dataset/data/ and extract it there — the
loader picks it up automatically, no environment variable needed:
cd MIA_on_dataset
for ds in voxpopuli spgispeech gigaspeech librispeech tedlium clotho cochlscene nsynth; do
hf download Snooow1029/MIA_LALM "${ds}_mia_dataset.tar.zst" \
--repo-type dataset --local-dir data
tar --zstd -xf "data/${ds}_mia_dataset.tar.zst" -C data
rm "data/${ds}_mia_dataset.tar.zst"
done
Each dataset then lives under MIA_on_dataset/data/<family>_mia_dataset/,
matching the manifest paths the runners expect (e.g.
voxpopuli_mia_dataset/tts_61_2/tts_dataset.json). To keep the data
elsewhere, extract anywhere and export AUDIO_MIA_DATA_ROOT=/that/path.
Layout
Each archive expands to <family>_mia_dataset/... containing audio plus the
JSON/CSV manifests. The same manifests are also available loose in this repo for
browsing.