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cs.SD2026
Sobolev Norms in Neural Embeddings Measure Audio Morphing Regularity
Théo Chasle Cauchy, Modan Tailleur, Barbara Pascal +2
Morphing has recently gained renewed interest with the emergence of generative models, particularly in audio and image generation. In musical sound synthesis, morphing can generate…
cs.LG2026
COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation
Ruike Cao, Fugen Yao, Liang Dong +3
While Large Language Models (LLMs) have achieved remarkable results across various benchmarks, their alignment with normative values often results in homogenized responses that fai…
cs.SD2026
Predicting Timbre Traits for Interpretable Assessment of Musical Sound Synthesizers
Théo Chasle Cauchy, Modan Tailleur, Lindsey Reymore +2
Measuring neural audio synthesizers' performance is now routinely conducted using distribution based metrics such as the Fréchet Audio Distance (FAD). Although this metric can be c…