Zobrazeno 1 - 10
of 51 333
pro vyhledávání: '"WANG, LIN"'
Distilling 3D representations from pretrained 2D diffusion models is essential for 3D creative applications across gaming, film, and interior design. Current SDS-based methods are hindered by inefficient information distillation from diffusion models
Externí odkaz:
http://arxiv.org/abs/2412.05929
Publikováno v:
Findings of the Association for Computational Linguistics: EMNLP 2024
Linear Text Segmentation is the task of automatically tagging text documents with topic shifts, i.e. the places in the text where the topics change. A well-established area of research in Natural Language Processing, drawing from well-understood conc
Externí odkaz:
http://arxiv.org/abs/2411.16613
Neural network force field models such as DeePMD have enabled highly efficient large-scale molecular dynamics simulations with ab initio accuracy. However, building such models heavily depends on the training data obtained by costly electronic struct
Externí odkaz:
http://arxiv.org/abs/2411.13850
Generating realistic and diverse road scenarios is essential for autonomous vehicle testing and validation. Nevertheless, owing to the complexity and variability of real-world road environments, creating authentic and varied scenarios for intelligent
Externí odkaz:
http://arxiv.org/abs/2411.09451
In the field of big data analytics, the search for efficient subdata selection methods that enable robust statistical inferences with minimal computational resources is of high importance. A procedure prior to subdata selection could perform variable
Externí odkaz:
http://arxiv.org/abs/2411.06298
Autor:
Wang, Lin, Wu, Zhengyan
We explore probabilistic approaches to the deterministic energy equality for the forced Surface Quasi-Geostrophic (SQG) equation on a torus. First, we prove the zero-noise dynamical large deviations for a corresponding stochastic SQG equation, where
Externí odkaz:
http://arxiv.org/abs/2411.04500
Multimodal conversation, a crucial form of human communication, carries rich emotional content, making the exploration of the causes of emotions within it a research endeavor of significant importance. However, existing research on the causes of emot
Externí odkaz:
http://arxiv.org/abs/2411.02430
The increasing concern for data privacy has driven the rapid development of federated learning (FL), a privacy-preserving collaborative paradigm. However, the statistical heterogeneity among clients in FL results in inconsistent performance of the se
Externí odkaz:
http://arxiv.org/abs/2410.20141
Blind face restoration (BFR) is a fundamental and challenging problem in computer vision. To faithfully restore high-quality (HQ) photos from poor-quality ones, recent research endeavors predominantly rely on facial image priors from the powerful pre
Externí odkaz:
http://arxiv.org/abs/2410.09864