Activation-patching prompt pairs (MusicCaps-derived)
Paper
TADA! Tuning Audio Diffusion Models through Activation Steering — https://huggingface.co/papers/2602.11910
3246 rows of (clean, corrupted) prompt pairs derived from the MusicCaps captions by swapping feature-bearing words (e.g. violin↔trumpet, female↔male, fast↔slow) using the mapping in src/preprocess/features.py.
Features covered (21): bongos, cello, drums, fast, female, flute, happy, harmonica, jazz, male… See the full description on the dataset page: https://huggingface.co/datasets/lukasz-staniszewski/patching-music-musiccaps-prompts.