Zobrazeno 1 - 10
of 6 186
pro vyhledávání: '"Wang, Yujie"'
Autor:
Zhou, Chijin, Zhang, Shuyang, Dai, Xueliang, Cao, Yixin, Yuan, Ye, Xia, Chengjie, Zeng, Zhikun, Wang, Yujie
Using high-resolution x-ray tomography, we experimentally investigate the bridge structures in tapped granular packings composed of particles with varying friction coefficients. We find that gravity can induce subtle structural changes on the load-be
Externí odkaz:
http://arxiv.org/abs/2409.18093
Disordered granular packings share many similarities with supercooled liquids, particu-larly in the rapid increase of structural relaxation time within a narrow range of temperature or packing fraction. However, it is unclear whether the dynamics of
Externí odkaz:
http://arxiv.org/abs/2409.04983
Autor:
Wang, Yujie, Zhu, Shenhan, Fu, Fangcheng, Miao, Xupeng, Zhang, Jie, Zhu, Juan, Hong, Fan, Li, Yong, Cui, Bin
Recent foundation models are capable of handling multiple machine learning (ML) tasks and multiple data modalities with the unified base model structure and several specialized model components. However, the development of such multi-task (MT) multi-
Externí odkaz:
http://arxiv.org/abs/2409.03365
Granular heaps are critical in both industrial applications and natural processes, exhibiting complex behaviors that have sparked significant research interest. The stress dip phenomenon observed beneath granular heaps continues to be a topic of sign
Externí odkaz:
http://arxiv.org/abs/2408.17147
Jamming transitions and the rheology of granular avalanches in fluids are investigated using experiments and numerical simulations. Simulations use the lattice-Boltzmann method coupled with the discrete element method, providing detailed stress and d
Externí odkaz:
http://arxiv.org/abs/2408.13730
Dynamic activation (DA) techniques, such as DejaVu and MoEfication, have demonstrated their potential to significantly enhance the inference efficiency of large language models (LLMs). However, these techniques often rely on ReLU activation functions
Externí odkaz:
http://arxiv.org/abs/2408.11393
In this paper, we propose a novel adaptive Control Barrier Function (CBF) based controller for nonlinear systems with complex, time-varying input constraints. Conventional CBF approaches often struggle with feasibility issues and stringent assumption
Externí odkaz:
http://arxiv.org/abs/2408.09534
Recent holographic display approaches propelled by deep learning have shown remarkable success in enabling high-fidelity holographic projections. However, these displays have still not been able to demonstrate realistic focus cues, and a major gap st
Externí odkaz:
http://arxiv.org/abs/2409.00028
Autor:
Lu, Haiyang, Yuan, Houfei, Zhang, Shuyang, Zeng, Zhikun, Xing, Yi, Xu, Jiazhao, Wang, Xin, Wang, Yujie
Using X-ray tomography, we experimentally investigate granular segregation phenomena in a mixture of particles with different densities under quasi-static cyclic shear. We quantitatively characterize their height distributions at steady states by min
Externí odkaz:
http://arxiv.org/abs/2407.10727
Massive Over-activation Yielded Uplifts(MOYU) is an inherent property of large language models, and dynamic activation(DA) based on the MOYU property is a clever yet under-explored strategy designed to accelerate inference in these models. Existing m
Externí odkaz:
http://arxiv.org/abs/2406.12569