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cs.SD2026
SongCraft: Unified Song Generation and Editing with Reconstructive Learning
Haohe Liu, Varun Nagaraja, Gael Le Lan +5
Song generation and editing have mostly been treated as separate tasks. Existing editing methods often require noise injection and regeneration or curated paired training data. We…
cs.SD2025
UniFlow-Audio: Unified Flow Matching for Audio Generation from Omni-Modalities
Xuenan Xu, Jiahao Mei, Zihao Zheng +9
Audio generation, including speech, music and sound effects, has advanced rapidly in recent years. These tasks can be divided into two categories: time-aligned (TA) tasks, where ea…
cs.SD2025
DualMark: Identifying Model and Training Data Origins in Generated Audio
Xuefeng Yang, Jian Guan, Feiyang Xiao +5
Existing watermarking methods for audio generative models only enable model-level attribution, allowing the identification of the originating generation model, but are unable to tr…