Zobrazeno 1 - 10
of 1 858
pro vyhledávání: '"ZHANG, JUE"'
Autor:
Chen, Yanting, Ren, Yi, Qin, Xiaoting, Zhang, Jue, Yuan, Kehong, Han, Lu, Lin, Qingwei, Zhang, Dongmei, Rajmohan, Saravan, Zhang, Qi
Video recordings of user activities, particularly desktop recordings, offer a rich source of data for understanding user behaviors and automating processes. However, despite advancements in Vision-Language Models (VLMs) and their increasing use in vi
Externí odkaz:
http://arxiv.org/abs/2411.08768
Autor:
Peng, Yingzhe, Qin, Xiaoting, Zhang, Zhiyang, Zhang, Jue, Lin, Qingwei, Yang, Xu, Zhang, Dongmei, Rajmohan, Saravan, Zhang, Qi
The rise of large language models (LLMs) has revolutionized user interactions with knowledge-based systems, enabling chatbots to synthesize vast amounts of information and assist with complex, exploratory tasks. However, LLM-based chatbots often stru
Externí odkaz:
http://arxiv.org/abs/2410.24032
Autor:
Lu, Junting, Zhang, Zhiyang, Yang, Fangkai, Zhang, Jue, Wang, Lu, Du, Chao, Lin, Qingwei, Rajmohan, Saravan, Zhang, Dongmei, Zhang, Qi
Multimodal large language models (MLLMs) have enabled LLM-based agents to directly interact with application user interfaces (UIs), enhancing agents' performance in complex tasks. However, these agents often suffer from high latency and low reliabili
Externí odkaz:
http://arxiv.org/abs/2409.17140
Autor:
Shandilya, Shivam, Xia, Menglin, Ghosh, Supriyo, Jiang, Huiqiang, Zhang, Jue, Wu, Qianhui, Rühle, Victor
The increasing prevalence of large language models (LLMs) such as GPT-4 in various applications has led to a surge in the size of prompts required for optimal performance, leading to challenges in computational efficiency. Prompt compression aims to
Externí odkaz:
http://arxiv.org/abs/2409.13035
Autor:
Jain, Kunal, Parayil, Anjaly, Mallick, Ankur, Choukse, Esha, Qin, Xiaoting, Zhang, Jue, Goiri, Íñigo, Wang, Rujia, Bansal, Chetan, Rühle, Victor, Kulkarni, Anoop, Kofsky, Steve, Rajmohan, Saravan
Large Language Model (LLM) workloads have distinct prefill and decode phases with different compute and memory requirements which should ideally be accounted for when scheduling input queries across different LLM instances in a cluster. However exist
Externí odkaz:
http://arxiv.org/abs/2408.13510
Autor:
Zhang, Zhiyang, Yang, Fangkai, Qin, Xiaoting, Zhang, Jue, Lin, Qingwei, Cheng, Gong, Zhang, Dongmei, Rajmohan, Saravan, Zhang, Qi
The Vision of Autonomic Computing (ACV), proposed over two decades ago, envisions computing systems that self-manage akin to biological organisms, adapting seamlessly to changing environments. Despite decades of research, achieving ACV remains challe
Externí odkaz:
http://arxiv.org/abs/2407.14402
Autor:
Fu, Jia, Qin, Xiaoting, Yang, Fangkai, Wang, Lu, Zhang, Jue, Lin, Qingwei, Chen, Yubo, Zhang, Dongmei, Rajmohan, Saravan, Zhang, Qi
Recent advancements in Large Language Models have transformed ML/AI development, necessitating a reevaluation of AutoML principles for the Retrieval-Augmented Generation (RAG) systems. To address the challenges of hyper-parameter optimization and onl
Externí odkaz:
http://arxiv.org/abs/2406.19251
Here we demonstrate the capacity to manipulate the optical spring (OS) effect by employing an optical parametric amplifier (OPA) within an optical cavity. We observed more than a factor of 2 increase in the OS frequency shift with the OPA. We also sh
Externí odkaz:
http://arxiv.org/abs/2406.14590
Autor:
Valliyakalayil, Jobin Thomas, Wade, Andrew, Rabeling, David, Zhang, Jue, Shaddock, Daniel, McKenzie, Kirk
Laser frequency noise suppression is a critical requirement for the Laser Interferometer Space Antenna (LISA) mission to detect gravitational waves. The baseline laser stabilization is achieved using cavity pre-stabilization and a post-processing tec
Externí odkaz:
http://arxiv.org/abs/2406.02261
Autor:
Liu, Shuhan, Zhou, Yunfan, Ying, Lu, Tian, Yuan, Zhang, Jue, Zhou, Shandan, Cui, Weiwei, Lin, Qingwei, Moscibroda, Thomas, Zhang, Haidong, Weng, Di, Wu, Yingcai
Finding the root causes of anomalies in cloud computing systems quickly is crucial to ensure availability and efficiency since accurate root causes can guide engineers to take appropriate actions to address the anomalies and maintain customer satisfa
Externí odkaz:
http://arxiv.org/abs/2405.15571