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iTAG flips the script on causally-annotated text generation, achieving both natural language and high annotation accuracy by treating the causal graph as the target and iteratively refining concept selection.
Forget error accumulation in long music sequences: anchoring generation to existing musical features unlocks significantly improved structural coherence and quality.
