5 papers
CAT-Flow: Curvature-Adaptive sTeps for Flow Matching
Qinchan Li, Pedro Cisneros-Velarde, Keru Fu +3
Flow Matching has emerged as a leading framework for generative modeling, powering state-of-the-art systems such as FLUX and Stable Diffusion 3.5. However, the iterative nature of…
SymTRELLIS: Symmetry-Enforced Voxel Latents for 3D Generation
Guangda Ji, Qimin Chen, Qinchan Li +3
Single-view 3D generative models have achieved impressive visual quality, yet they are not designed to satisfy structural or functional requirements, and in practice, often fall sh…
Cost-Aware Routing for Efficient Text-To-Image Generation
Qinchan Li, Kenneth Chen, Changyue Su +3
Diffusion models are well known for their ability to generate a high-fidelity image for an input prompt through an iterative denoising process. Unfortunately, the high fidelity als…
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models
Qinchan Li, Kenneth Chen, Changyue Su +1
Diffusion models have shown unprecedented success in the task of text-to-image generation. While these models are capable of generating high-quality and realistic images, the compl…
ERAS: Evaluating the Robustness of Chinese NLP Models to Morphological Garden Path Errors
Qinchan Li, Sophie Hao
In languages without orthographic word boundaries, NLP models perform word segmentation, either as an explicit preprocessing step or as an implicit step in an end-to-end computatio…