Dan-Ni Zhao

MUUNRiver-Bench is presented, a diagnostic benchmark whose reference-audio queries use natural-language instructions to define relevance, and task-wise rank reversals reveal complementary biases: acoustic encoders favour local identity, whereas text-aligned encoders favour semantic relations.

A neuro-symbolic approach boosts the quality of twelve-tone music generation, elevating output consistency and expert preference significantly.