STEMMA-Bench / README.md
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metadata
license: cc-by-nc-sa-4.0
language:
  - en
pretty_name: STEMMA-Bench
size_categories:
  - n<1K
task_categories:
  - audio-text-to-text
  - question-answering
tags:
  - music
  - multi-audio
  - benchmark
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test.jsonl
dataset_info:
  features:
    - name: id
      dtype: string
    - name: task
      dtype: string
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: audios
      sequence: string
  splits:
    - name: test
      num_examples: 300

STEMMA-Bench

πŸ“„ Paper  |  πŸ’» Code  |  πŸ€— STEMMA-Instruct  |  πŸ€— STEMMA-MF2601  |  πŸ€— STEMMA-MOSS-Music

Multi-audio music relation benchmark from STEMMA: Song-to-Stem Multi-Audio Reasoning for Large Audio Language Models. Each item has an anchor (Audio A) and four candidates (Candidate B–E), one correct (chance 25%). Clips are sections and native stems of multitrack recordings; every item was checked by listening.

Items 300 (100 each from MUSDB18-HQ, MoisesDB, MedleyDB)
Structural / attribute 127 / 173
Tasks 14

Format

Field Description
id item ID
task <relation>_anchor_candidates_mcq
question prompt with five <audio> (Audio A, Candidate B–E)
answer correct letter (B–E)
audios audio IDs, in prompt order

Structural tasks: same_track, same_track_block, adjacent_master, adjacent_block, same_section_cross_role, parent_child; the rest are attribute tasks (key, tempo, instrument, genre). _block tasks use stems. Accuracy is reported per group; predicting A counts as wrong.

Audio

Audio is not included. Audio IDs are <corpus>/<track>/<section>[/<stem>]; metadata/audio.jsonl gives each clip's source files in the original corpus, start/end time, and whether summed stems are peak-normalized. 210 MedleyDB section mixes come from the mixture files in seungheondoh/cmd-medleydb-metadata (revision 99e4ae2).

Citation

@misc{sohn2026stemma,
  title         = {{STEMMA}: Song-to-Stem Multi-Audio Reasoning for Large Audio Language Models},
  author        = {Sohn, Hoyeol and Kim, Wonil and Kim, Keunhyoung and Kum, Sangeun and Kim, Taehyoung and Moon, Dongjoo and Charoenchob, Theerasak and Weerapang, Teeratep and Lee, Jongpil and Nam, Juhan},
  year          = {2026},
  eprint        = {2610.11884},
  archivePrefix = {arXiv},
  primaryClass  = {cs.SD},
  url           = {https://arxiv.org/abs/2610.11884}
}

License

CC BY-NC-SA 4.0. The audio remains subject to the MUSDB18-HQ, MoisesDB, and MedleyDB terms.