ARIA decomposes music training data attribution into musical aspects and supplies reliability diagnostics from similarity metrics and score matrix analysis, with validation on symbolic models using counterfactual retraining.
Dornis and Sebastian Stober
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
roles
background 2representative citing papers
FEST improves RLVR sample efficiency on math and coding benchmarks by combining supervised signals, on-policy signals, and decaying weights on just 128 randomly chosen demonstrations, matching full-dataset baselines.