Zobrazeno 1 - 10
of 5 273
pro vyhledávání: '"ZHANG, ZHIWEI"'
It is challenging to scale Ising machines for industrial-level problems due to algorithm or hardware limitations. Although higher-order Ising models provide a more compact encoding, they are, however, hard to physically implement. This work proposes
Externí odkaz:
http://arxiv.org/abs/2412.13489
Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a comprehensive
Externí odkaz:
http://arxiv.org/abs/2411.02006
Autor:
Wang, Fali, Zhang, Zhiwei, Zhang, Xianren, Wu, Zongyu, Mo, Tzuhao, Lu, Qiuhao, Wang, Wanjing, Li, Rui, Xu, Junjie, Tang, Xianfeng, He, Qi, Ma, Yao, Huang, Ming, Wang, Suhang
Large language models (LLM) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their proficiency in various tasks, LLMs like LaPM 540B and Llama-3.1 405B face li
Externí odkaz:
http://arxiv.org/abs/2411.03350
Traffic forecasting plays a key role in Intelligent Transportation Systems, and significant strides have been made in this field. However, most existing methods can only predict up to four hours in the future, which doesn't quite meet real-world dema
Externí odkaz:
http://arxiv.org/abs/2411.00844
Autor:
Zhang, Zhiwei, Wang, Fali, Li, Xiaomin, Wu, Zongyu, Tang, Xianfeng, Liu, Hui, He, Qi, Yin, Wenpeng, Wang, Suhang
Large language models (LLMs) have shown remarkable proficiency in generating text, benefiting from extensive training on vast textual corpora. However, LLMs may also acquire unwanted behaviors from the diverse and sensitive nature of their training d
Externí odkaz:
http://arxiv.org/abs/2410.16454
Graph Prompt Learning (GPL) has been introduced as a promising approach that uses prompts to adapt pre-trained GNN models to specific downstream tasks without requiring fine-tuning of the entire model. Despite the advantages of GPL, little attention
Externí odkaz:
http://arxiv.org/abs/2410.13974
The quality of training data significantly impacts the performance of large language models (LLMs). There are increasing studies using LLMs to rate and select data based on several human-crafted metrics (rules). However, these conventional rule-based
Externí odkaz:
http://arxiv.org/abs/2410.04715
Autor:
Xu, Zijun, Jin, Rui, Wu, Ke, Zhao, Yi, Zhang, Zhiwei, Zhao, Jieru, Gao, Fei, Gan, Zhongxue, Ding, Wenchao
In complex missions such as search and rescue,robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings. High-quality and real-time reconstruction enhances situational aware
Externí odkaz:
http://arxiv.org/abs/2409.17624
Multi-robot swarms utilize swarm intelligence to collaborate on tasks and play an increasingly significant role in a variety of practical scenarios. However, due to the complex design, multi-robot swarm systems often have vulnerabilities caused by lo
Externí odkaz:
http://arxiv.org/abs/2409.04736
Autor:
Zhang, Zhiwei
Class imbalance is a critical issue in image classification that significantly affects the performance of deep recognition models. In this work, we first identify a network degeneration dilemma that hinders the model learning by introducing a high li
Externí odkaz:
http://arxiv.org/abs/2408.17197