Zobrazeno 1 - 10
of 13 504
pro vyhledávání: '"XU, Qiang"'
Autor:
Chen, Yongshuo, Ma, Cheng, Cui, Boning, Cui, Tian, Mi, Wenhui, Xu, Qiang, Wang, Yanchao, Ma, Yanming
Nonlocal kinetic energy density functionals (KEDFs) with density-dependent kernels are currently the most accurate functionals available for orbital-free density functional theory (OF-DFT) calculations. However, despite advances in numerical techniqu
Externí odkaz:
http://arxiv.org/abs/2412.02959
Recently, text-to-image models based on diffusion have achieved remarkable success in generating high-quality images. However, the challenge of personalized, controllable generation of instances within these images remains an area in need of further
Externí odkaz:
http://arxiv.org/abs/2411.15252
The rapid advancement of diffusion models has greatly improved video synthesis, especially in controllable video generation, which is essential for applications like autonomous driving. However, existing methods are limited by scalability and how con
Externí odkaz:
http://arxiv.org/abs/2411.13807
Circuit representation learning is increasingly pivotal in Electronic Design Automation (EDA), serving various downstream tasks with enhanced model efficiency and accuracy. One notable work, DeepSeq, has pioneered sequential circuit learning by encod
Externí odkaz:
http://arxiv.org/abs/2411.00530
Continual learning requires to overcome catastrophic forgetting when training a single model on a sequence of tasks. Recent top-performing approaches are prompt-based methods that utilize a set of learnable parameters (i.e., prompts) to encode task k
Externí odkaz:
http://arxiv.org/abs/2410.20444
Autor:
Xu, Qiang, Hurtut, Thomas
In the digital landscape, the ubiquity of data visualizations in media underscores the necessity for accessibility to ensure inclusivity for all users, including those with visual impairments. Current visual content often fails to cater to the needs
Externí odkaz:
http://arxiv.org/abs/2409.17494
Whole-body multimodal motion generation, controlled by text, speech, or music, has numerous applications including video generation and character animation. However, employing a unified model to achieve various generation tasks with different conditi
Externí odkaz:
http://arxiv.org/abs/2407.21136
Autor:
Cui, Fan, Yin, Chenyang, Zhou, Kexing, Xiao, Youwei, Sun, Guangyu, Xu, Qiang, Guo, Qipeng, Song, Demin, Lin, Dahua, Zhang, Xingcheng, Yun, Liang
Recent studies have demonstrated the significant potential of Large Language Models (LLMs) in generating Register Transfer Level (RTL) code, with notable advancements showcased by commercial models such as GPT-4 and Claude3-Opus. However, these propr
Externí odkaz:
http://arxiv.org/abs/2407.16237
This is the technique report for the winning solution of the CVPR2024 GenAI Media Generation Challenge Workshop's Instruction-guided Image Editing track. Instruction-guided image editing has been largely studied in recent years. The most advanced met
Externí odkaz:
http://arxiv.org/abs/2407.13139
Circuit representation learning has shown promising results in advancing the field of Electronic Design Automation (EDA). Existing models, such as DeepGate Family, primarily utilize Graph Neural Networks (GNNs) to encode circuit netlists into gate-le
Externí odkaz:
http://arxiv.org/abs/2407.11095