Zobrazeno 1 - 10
of 3 169
pro vyhledávání: '"Weizhu An"'
Autor:
Yang, Yaming, Muhtar, Dilxat, Shen, Yelong, Zhan, Yuefeng, Liu, Jianfeng, Wang, Yujing, Sun, Hao, Deng, Denvy, Sun, Feng, Zhang, Qi, Chen, Weizhu, Tong, Yunhai
Parameter-efficient fine-tuning (PEFT) has been widely employed for domain adaptation, with LoRA being one of the most prominent methods due to its simplicity and effectiveness. However, in multi-task learning (MTL) scenarios, LoRA tends to obscure t
Externí odkaz:
http://arxiv.org/abs/2410.09437
Time series imputation is important for numerous real-world applications. To overcome the limitations of diffusion model-based imputation methods, e.g., slow convergence in inference, we propose a novel method for time series imputation in this work,
Externí odkaz:
http://arxiv.org/abs/2410.07550
We propose a normalized deep neural network (norm-DNN) for computing ground states of Bose-Einstein condensation (BEC) via the minimization of the Gross-Pitaevskii energy functional under unitary mass normalization. Compared with the traditional deep
Externí odkaz:
http://arxiv.org/abs/2410.05319
We consider a two-dimensional sharp-interface model for solid-state dewetting of thin films with anisotropic surface energies on curved substrates, where the film/vapor interface and substrate surface are represented by an evolving and a static curve
Externí odkaz:
http://arxiv.org/abs/2410.00438
Autor:
Liu, Liyuan, Kim, Young Jin, Wang, Shuohang, Liang, Chen, Shen, Yelong, Cheng, Hao, Liu, Xiaodong, Tanaka, Masahiro, Wu, Xiaoxia, Hu, Wenxiang, Chaudhary, Vishrav, Lin, Zeqi, Zhang, Chenruidong, Xue, Jilong, Awadalla, Hany, Gao, Jianfeng, Chen, Weizhu
Mixture-of-Experts (MoE) models scale more effectively than dense models due to sparse computation through expert routing, selectively activating only a small subset of expert modules. However, sparse computation challenges traditional training pract
Externí odkaz:
http://arxiv.org/abs/2409.12136
We study the dynamics of a small solid particle arising from the dewetting of a thin film on a curved substrate driven by capillarity, where mass transport is controlled by surface diffusion. We consider the case when the size of the deposited partic
Externí odkaz:
http://arxiv.org/abs/2409.03468
Publikováno v:
Journal of Computational Physics, 519(2024), 113422
Solving real-world nonlinear semiconductor device problems modeled by the drift-diffusion equations coupled with the Poisson equation (also known as the Poisson-Nernst-Planck equations) necessitates an accurate and efficient numerical scheme which ca
Externí odkaz:
http://arxiv.org/abs/2408.09692
We propose and analyze an efficient and accurate numerical method for computing ground states of spin-2 Bose-Einstein condensates (BECs) by using the normalized gradient flow (NGF). In order to successfully extend the NGF to spin-2 BECs which has fiv
Externí odkaz:
http://arxiv.org/abs/2407.14441
Autor:
Luo, Haipeng, Sun, Qingfeng, Xu, Can, Zhao, Pu, Lin, Qingwei, Lou, Jianguang, Chen, Shifeng, Tang, Yansong, Chen, Weizhu
Assessing the effectiveness of large language models (LLMs) presents substantial challenges. The method of conducting human-annotated battles in an online Chatbot Arena is a highly effective evaluative technique. However, this approach is limited by
Externí odkaz:
http://arxiv.org/abs/2407.10627
Efficiently modeling sequences with infinite context length has been a long-standing problem. Past works suffer from either the quadratic computation complexity or the limited extrapolation ability on length generalization. In this work, we present S
Externí odkaz:
http://arxiv.org/abs/2406.07522