7 papers · 1 filter
DARTree: Speculative Diffusion Decoding with Autoregressive Draft Trees
Tianyi Li, Yaxin Luo, Xinyi Shang +1
Speculative decoding losslessly accelerates autoregressive language models by verifying multiple draft tokens in parallel. Diffusion-based drafters further reduce proposal latency…
Three-Body Scattering for Generative Modeling
Peng Sun, Zhenglin Cheng, Deyuan Liu +3
Modern generative models typically rely on an adversarial critic, a prescribed noise-to-data path, or an autoregressive factorization. Instead, we show that a proper distributional…
Fast and Scalable Analytical Diffusion
Xinyi Shang, Peng Sun, Jingyu Lin +1
Analytical diffusion models offer a mathematically transparent path to generative modeling by formulating the denoising score as an empirical-Bayes posterior mean. However, this in…
Duality Models: An Embarrassingly Simple One-step Generation Paradigm
Peng Sun, Xinyi Shang, Tao Lin +1
Consistency-based generative models like Shortcut and MeanFlow achieve impressive results via a target-aware design for solving the Probability Flow ODE (PF-ODE). Typically, such m…
Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense
Jiacheng Liu, Yaxin Luo, Jiacheng Cui +3
The rapid evolution of GUI-enabled agents has rendered traditional CAPTCHAs obsolete. While previous benchmarks like OpenCaptchaWorld established a baseline for evaluating multimod…
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…