DisciplineGen-1M is a million-scale multidisciplinary dataset for text-to-image generation and editing, paired with a discipline-informed model that improves results on discipline-specific benchmarks.
Tunesformer: Form- ing irish tunes with control codes by bar patching
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A two-stage framework uses an LLM to plan musical structures from text and then generates conditioned ABC notation sheet music, outperforming baselines in expert-validated evaluations.
ONOTE is a multi-format benchmark that applies a deterministic pipeline to expose a disconnect between perceptual accuracy and music-theoretic comprehension in leading omnimodal AI models.
Anchored Cyclic Generation uses anchor features from known music to mitigate error accumulation in autoregressive models, with the Hi-ACG framework delivering better long-sequence symbolic music and music completion performance.
citing papers explorer
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DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing
DisciplineGen-1M is a million-scale multidisciplinary dataset for text-to-image generation and editing, paired with a discipline-informed model that improves results on discipline-specific benchmarks.
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Text2Score: Generating Sheet Music From Textual Prompts
A two-stage framework uses an LLM to plan musical structures from text and then generates conditioned ABC notation sheet music, outperforming baselines in expert-validated evaluations.
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ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence
ONOTE is a multi-format benchmark that applies a deterministic pipeline to expose a disconnect between perceptual accuracy and music-theoretic comprehension in leading omnimodal AI models.
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Anchored Cyclic Generation: A Novel Paradigm for Long-Sequence Symbolic Music Generation
Anchored Cyclic Generation uses anchor features from known music to mitigate error accumulation in autoregressive models, with the Hi-ACG framework delivering better long-sequence symbolic music and music completion performance.