37 citations · 64 across the 6 of their papers we have counts for
7 papers
Fast-dVLA: Accelerating Discrete Diffusion VLA to Real-Time Performance
Wenxuan Song, Jiayi Chen, Shuai Chen +8
This paper proposes a novel approach to address the challenge that pretrained VLA models often fail to effectively improve performance and reduce adaptation costs during standard s…
Multimodal Dataset Distillation via Phased Teacher Models
Shengbin Guo, Hang Zhao, Senqiao Yang +5
Multimodal dataset distillation aims to construct compact synthetic datasets that enable efficient compression and knowledge transfer from large-scale image-text data. However, exi…
MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation
Yang Liu, Pengxiang Ding, Tengyue Jiang +10
Vision-Language-Action (VLA) models map visual observations and natural-language instructions to robot actions; however, hierarchical and autoregressive paradigms often incur archi…
PIXART-δ: Fast and Controllable Image Generation with Latent Consistency Models
Junsong Chen, Yue Wu, Simian Luo +5
This technical report introduces PIXART-δ, a text-to-image synthesis framework that integrates the Latent Consistency Model (LCM) and ControlNet into the advanced PIXART-α model. P…
LCM-LoRA: A Universal Stable-Diffusion Acceleration Module
Simian Luo, Yiqin Tan, Suraj Patil +6
Latent Consistency Models (LCMs) have achieved impressive performance in accelerating text-to-image generative tasks, producing high-quality images with minimal inference steps. LC…
Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference
Simian Luo, Yiqin Tan, Longbo Huang +2
Latent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-resolution images. However, the iterative sampling process is computationally intensive and lea…
Large Trajectory Models are Scalable Motion Predictors and Planners
Qiao Sun, Shiduo Zhang, Danjiao Ma +7
Motion prediction and planning are vital tasks in autonomous driving, and recent efforts have shifted to machine learning-based approaches. The challenges include understanding div…