Real-world voice separation must recover individual voices from overlapping speech, environmental noise, and music, yet isolated source recordings are rarely available for supervision. We introduce Soloist, a generative model for blind voice separation that autoregressively generates individual voice streams as audio-c...
Chenchen Yang, Chu-Fan Yu, Bo-Tian Jiang et al.· 0 citations
The MiMo-V2.6 series is introduced, an omni-modal family that pushes the frontier of model intelligence by scaling RL compute by building infrastructure for mixed-task agentic RL, including a unified trajectory representation, high-concurrency multi-framework rollout, decoupled control and data planes, and training-inf...
Xiao-Zhen Qiao, Zi-Yue Hua, Zi-Rui Ou et al.· 10 citations
OmniVAE is presented, a jointly trained audio-video VAE that learns fine-grained semantic alignment between audio and video latent representations that translates into higher generation quality and more accurate cross-modal synchronization in downstream text-to-audio-video generation.
Jun Zhan, Chenchen Yang, Yitian Gong et al.· arXiv.org· 0 citations
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