1 citations · 1 across the 19 of their papers we have counts for
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Optimizing Decoding Paths in Masked Diffusion Models by Quantifying Uncertainty
Ziyu Chen, Xinbei Jiang, Peng Sun +1
Masked Diffusion Models (MDMs) offer flexible, non-autoregressive generation, but this freedom introduces a challenge: final output quality is highly sensitive to the decoding orde…
Unified Continuous Generative Models
Peng Sun, Yi Jiang, Tao Lin
Recent advances in continuous generative models, including multi-step approaches like diffusion and flow-matching (typically requiring 8-1000 sampling steps) and few-step methods s…
Equally Critical: Samples, Targets, and Their Mappings in Datasets
Runkang Yang, Peng Sun, Xinyi Shang +2
Data inherently possesses dual attributes: samples and targets. For targets, knowledge distillation has been widely employed to accelerate model convergence, primarily relying on t…
Collaborative Unlabeled Data Optimization
Xinyi Shang, Peng Sun, Fengyuan Liu +1
This paper pioneers a novel data-centric paradigm to maximize the utility of unlabeled data, tackling a critical question: How can we enhance the efficiency and sustainability of d…
Efficient Generative Model Training via Embedded Representation Warmup
Deyuan Liu, Peng Sun, Xufeng Li +1
Generative models face a fundamental challenge: they must simultaneously learn high-level semantic concepts (what to generate) and low-level synthesis details (how to generate it).…