Zobrazeno 1 - 10
of 10 774
pro vyhledávání: '"JIN, Peng"'
Autor:
Pang, Yatian, Jin, Peng, Yang, Shuo, Lin, Bin, Zhu, Bin, Tang, Zhenyu, Chen, Liuhan, Tay, Francis E. H., Lim, Ser-Nam, Yang, Harry, Yuan, Li
Autoregressive models, built based on the Next Token Prediction (NTP) paradigm, show great potential in developing a unified framework that integrates both language and vision tasks. In this work, we rethink the NTP for autoregressive image generatio
Externí odkaz:
http://arxiv.org/abs/2412.15321
Intelligent metamaterials have attracted widespread research interest due to their self-adaptive capabilities and controllability. They hold great potential for advancing fluid control by providing responsive and flexible solutions. However, current
Externí odkaz:
http://arxiv.org/abs/2412.02964
Manipulating particles, such as cells and tissues, in a flowing liquid environment is crucial for life science research. Traditional contactless tweezers, although widely used for single-cell manipulation, face several challenges. These include poten
Externí odkaz:
http://arxiv.org/abs/2412.00130
Autor:
Yan, Zhiyuan, Wang, Jiangming, Wang, Zhendong, Jin, Peng, Zhang, Ke-Yue, Chen, Shen, Yao, Taiping, Ding, Shouhong, Wu, Baoyuan, Yuan, Li
Existing AI-generated image (AIGI) detection methods often suffer from limited generalization performance. In this paper, we identify a crucial yet previously overlooked asymmetry phenomenon in AIGI detection: during training, models tend to quickly
Externí odkaz:
http://arxiv.org/abs/2411.15633
Autor:
He, Junwen, Wang, Yifan, Wang, Lijun, Lu, Huchuan, He, Jun-Yan, Li, Chenyang, Chen, Hanyuan, Lan, Jin-Peng, Luo, Bin, Geng, Yifeng
Text logo design heavily relies on the creativity and expertise of professional designers, in which arranging element layouts is one of the most important procedures. However, few attention has been paid to this specific task which needs to take prec
Externí odkaz:
http://arxiv.org/abs/2411.11435
Large language models have demonstrated substantial advancements in reasoning capabilities, particularly through inference-time scaling, as illustrated by models such as OpenAI's o1. However, current Vision-Language Models (VLMs) often struggle to pe
Externí odkaz:
http://arxiv.org/abs/2411.10440
Modeling and simulating the protein folding process overall remains a grand challenge in computational biology. We systematically investigate end-to-end quantum algorithms for simulating various protein dynamics with effects, such as mechanical force
Externí odkaz:
http://arxiv.org/abs/2411.03972
In this work, we upgrade the multi-head attention mechanism, the core of the Transformer model, to improve efficiency while maintaining or surpassing the previous accuracy level. We show that multi-head attention can be expressed in the summation for
Externí odkaz:
http://arxiv.org/abs/2410.11842
In this work, we aim to simultaneously enhance the effectiveness and efficiency of Mixture-of-Experts (MoE) methods. To achieve this, we propose MoE++, a general and heterogeneous MoE framework that integrates both Feed-Forward Network~(FFN) and zero
Externí odkaz:
http://arxiv.org/abs/2410.07348
Autor:
Liu, Zhoufei, Jin, Peng, Lei, Min, Wang, Chengmeng, Marchesoni, Fabio, Jiang, Jian-Hua, Huang, Jiping
Publikováno v:
Nat. Rev. Phys. 6, 554-565 (2024)
Thermal transport is a fundamental mechanism of energy transfer process quite distinct from wave propagation phenomena. It can be manipulated well beyond the possibilities offered by natural materials with a new generation of artificial metamaterials
Externí odkaz:
http://arxiv.org/abs/2409.00963