4 papers
NormGuard: Reward-Preserving Norm Constraints in Flow-Matching Reinforcement Learning
Tianlin Pan, Lianyu Pang, Cheng Da +4
Reinforcement learning (RL) post-training improves the reward alignment of flow-based generators, but often degrades perceptual quality in ways that are not captured by the reward…
MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training
Lianyu Pang, Tianlin Pan, Cheng Da +5
Representation alignment with pretrained vision models has recently shown strong potential for accelerating diffusion transformer training. By aligning intermediate diffusion featu…
Training for Identity, Inference for Controllability: A Unified Approach to Tuning-Free Face Personalization
Lianyu Pang, Ji Zhou, Qiping Wang +4
Tuning-free face personalization methods have developed along two distinct paradigms: text embedding approaches that map facial features into the text embedding space, and adapter-…
Tiny Model, Big Logic: Diversity-Driven Optimization Elicits Large-Model Reasoning Ability in VibeThinker-1.5B
Sen Xu, Yi Zhou, Wei Wang +7
Challenging the prevailing consensus that small models inherently lack robust reasoning, this report introduces VibeThinker-1.5B, a 1.5B-parameter dense model developed via our Spe…