Zobrazeno 1 - 10
of 1 112
pro vyhledávání: '"Ruisi P."'
Accurate channel models are the prerequisite for communication-theoretic investigations as well as system design. Channel modeling generally relies on statistical and deterministic approaches. However, there are still significant limits for the tradi
Externí odkaz:
http://arxiv.org/abs/2411.11798
Autor:
Zhang, Ruisi, Liu, Tianyu, Feng, Will, Gu, Andrew, Purandare, Sanket, Liang, Wanchao, Massa, Francisco
Distributed training of large models consumes enormous computation resources and requires substantial engineering efforts to compose various training techniques. This paper presents SimpleFSDP, a PyTorch-native compiler-based Fully Sharded Data Paral
Externí odkaz:
http://arxiv.org/abs/2411.00284
Autor:
Cai, Ruisi, Ro, Yeonju, Kim, Geon-Woo, Wang, Peihao, Bejnordi, Babak Ehteshami, Akella, Aditya, Wang, Zhangyang
The proliferation of large language models (LLMs) has led to the adoption of Mixture-of-Experts (MoE) architectures that dynamically leverage specialized subnetworks for improved efficiency and performance. Despite their benefits, MoE models face sig
Externí odkaz:
http://arxiv.org/abs/2410.19123
Autor:
Zhang, Ruisi, Koushanfar, Farinaz
The widely adopted and powerful generative large language models (LLMs) have raised concerns about intellectual property rights violations and the spread of machine-generated misinformation. Watermarking serves as a promising approch to establish own
Externí odkaz:
http://arxiv.org/abs/2410.19096
The space-air-ground integrated network (SAGIN) greatly improves coverage and reliability for millimeter-wave (mmWave) communication in high-speed railway (HSR) scenarios. However, a significant challenge arises in the transmission scheduling due to
Externí odkaz:
http://arxiv.org/abs/2410.12246
Autor:
Zhao, Xinyu, Sun, Guoheng, Cai, Ruisi, Zhou, Yukun, Li, Pingzhi, Wang, Peihao, Tan, Bowen, He, Yexiao, Chen, Li, Liang, Yi, Chen, Beidi, Yuan, Binhang, Wang, Hongyi, Li, Ang, Wang, Zhangyang, Chen, Tianlong
As Large Language Models (LLMs) excel across tasks and specialized domains, scaling LLMs based on existing models has garnered significant attention, which faces the challenge of decreasing performance when combining disparate models. Various techniq
Externí odkaz:
http://arxiv.org/abs/2410.05357
High-speed train (HST) has garnered significant attention from both academia and industry due to the rapid development of railways worldwide. Millimeter wave (mmWave) communication, known for its large bandwidth is an effective way to address perform
Externí odkaz:
http://arxiv.org/abs/2409.06946
This study investigates a networked integrated sensing and communication (ISAC) system, where multiple base stations (BSs), connected to a central processor (CP) via capacity-limited fronthaul links, cooperatively serve communication users while simu
Externí odkaz:
http://arxiv.org/abs/2408.08057
This paper presents AutoMarks, an automated and transferable watermarking framework that leverages graph neural networks to reduce the watermark search overheads during the placement stage. AutoMarks's novel automated watermark search is accomplished
Externí odkaz:
http://arxiv.org/abs/2407.20544
For one to guarantee higher-quality software development processes, risk management is essential. Furthermore, risks are those that could negatively impact an organization's operations or a project's progress. The appropriate prioritisation of softwa
Externí odkaz:
http://arxiv.org/abs/2406.09463