5 papers
Optimizing Few-Step Generation with Adaptive Matching Distillation
Lichen Bai, Zikai Zhou, Shitong Shao +5
Distribution Matching Distillation (DMD) is a powerful acceleration paradigm, yet its stability is often compromised in Forbidden Zone, regions where the real teacher provides unre…
NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation
Huichao Zhang, Liao Qu, Yiheng Liu +33
We present NextFlow, a unified decoder-only autoregressive transformer trained on 6 trillion interleaved text-image discrete tokens. By leveraging a unified vision representation w…
IMTalker: Efficient Audio-driven Talking Face Generation with Implicit Motion Transfer
Bo Chen, Tao Liu, Qi Chen +2
Talking face generation aims to synthesize realistic speaking portraits from a single image, yet existing methods often rely on explicit optical flow and local warping, which fail…
XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation
Bowen Chen, Mengyi Zhao, Haomiao Sun +4
Achieving fine-grained control over subject identity and semantic attributes (pose, style, lighting) in text-to-image generation, particularly for multiple subjects, often undermin…
MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
Fang-Duo Tsai, Shih-Lun Wu, Weijaw Lee +4
We propose MuseControlLite, a lightweight mechanism designed to fine-tune text-to-music generation models for precise conditioning using various time-varying musical attributes and…