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Generative AI like the Large Language Models (LLMs) has become more available for the general consumer in recent years. Publicly available services, e.g., ChatGPT, perform token generation on networked cloud server hardware, effectively…

机器学习 · 计算机科学 2024-12-23 Liam Seymour , Basar Kutukcu , Sabur Baidya

Large Language Models (LLMs) have demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in recent years. Despite the fact that most LLMs are trained…

计算与语言 · 计算机科学 2023-10-25 Xiang Zhang , Senyu Li , Bradley Hauer , Ning Shi , Grzegorz Kondrak

The evolution of wireless networks gravitates towards connected intelligence, a concept that envisions seamless interconnectivity among humans, objects, and intelligence in a hyper-connected cyber-physical world. Edge artificial…

信息论 · 计算机科学 2023-12-27 Yifei Shen , Jiawei Shao , Xinjie Zhang , Zehong Lin , Hao Pan , Dongsheng Li , Jun Zhang , Khaled B. Letaief

Large Language Models (LLMs) like GPT-3 and GPT-4 have emerged as groundbreaking innovations with capabilities that extend far beyond traditional AI applications. These sophisticated models, trained on massive datasets, can generate…

软件工程 · 计算机科学 2025-05-21 Md Asraful Haque

Large language models (LLMs) such as ChatGPT, Gemini, LlaMa, and Claude are trained on massive quantities of text parsed from the internet and have shown a remarkable ability to respond to complex prompts in a manner often indistinguishable…

光学 · 物理学 2025-04-01 Darui Lu , Yang Deng , Jordan M. Malof , Willie J. Padilla

Large language models (LLMs) have demonstrated exceptional performance across a variety of tasks. However, their substantial scale leads to significant computational resource consumption during inference, resulting in high costs.…

机器学习 · 计算机科学 2025-06-13 Zhaode Wang , Jingbang Yang , Xinyu Qian , Shiwen Xing , Xiaotang Jiang , Chengfei Lv , Shengyu Zhang

In recent years, Large Language Models (LLMs) have made significant strides towards Artificial General Intelligence. However, training these models from scratch requires substantial computational resources and vast amounts of text data. In…

计算与语言 · 计算机科学 2024-10-03 Wenzhen Zheng , Wenbo Pan , Xu Xu , Libo Qin , Li Yue , Ming Zhou

Deploying Large Language Models (LLMs) for question answering (QA) over lengthy contexts is a significant challenge. In industrial settings, this process is often hindered by high computational costs and latency, especially when multiple…

计算与语言 · 计算机科学 2025-09-29 Xiliang Zhu , Shi Zong , David Rossouw

Deploying Large Language Models (LLMs) on edge or mobile devices offers significant benefits, such as enhanced data privacy and real-time processing capabilities. However, it also faces critical challenges due to the substantial memory…

机器学习 · 计算机科学 2024-05-07 Yu Mao , Weilan Wang , Hongchao Du , Nan Guan , Chun Jason Xue

Models like GPT-4o enable real-time interaction with large language models (LLMs) through speech, significantly enhancing user experience compared to traditional text-based interaction. However, there is still a lack of exploration on how…

计算与语言 · 计算机科学 2025-03-04 Qingkai Fang , Shoutao Guo , Yan Zhou , Zhengrui Ma , Shaolei Zhang , Yang Feng

Large Language Models (LLMs) contribute significantly to the development of conversational AI and has great potentials to assist the scientific research in various areas. This paper attempts to address the following questions: What…

量子物理 · 物理学 2023-07-18 Zhiding Liang , Jinglei Cheng , Rui Yang , Hang Ren , Zhixin Song , Di Wu , Xuehai Qian , Tongyang Li , Yiyu Shi

The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advancements in open-source models has been challenging. This…

Large Language Models (LLMs) have garnered considerable interest within both academic and industrial. Yet, the application of LLMs to graph data remains under-explored. In this study, we evaluate the capabilities of four LLMs in addressing…

人工智能 · 计算机科学 2023-09-12 Chang Liu , Bo Wu

The manufacturing industry is undergoing a transformative shift, driven by cutting-edge technologies like 5G, AI, and cloud computing. Despite these advancements, effective system control, which is crucial for optimizing production…

机器人学 · 计算机科学 2025-03-07 Muhammad Waseem , Kshitij Bhatta , Chen Li , Qing Chang

Rapid advancements in large language models (LLMs) have increased interest in deploying them on mobile devices for on-device AI applications. Mobile users interact differently with LLMs compared to desktop users, creating unique…

Large Language Models (LLMs) excel at producing broadly relevant text, but this generality becomes a limitation when user-specific preferences are required, such as recommending restaurants or planning travel. In these scenarios, users…

Much worldly semantic knowledge can be encoded in large language models (LLMs). Such information could be of great use to robots that want to carry out high-level, temporally extended commands stated in natural language. However, the lack…

机器人学 · 计算机科学 2024-03-28 Ehsan Latif

Mobile phones are the most ubiquitous end devices, generating vast amounts of human-authored data and serving as the primary platform for end-side applications. As high-quality public data for large language models (LLMs) approaches…

机器学习 · 计算机科学 2025-12-10 Jiaxiang Geng , Lunyu Zhao , Yiyi Lu , Bing Luo

Large language models (LLMs) are now accessible to anyone with a computer, a web browser, and an internet connection via browser-based interfaces, shifting the dynamics of participation in AI development. This article examines how…

人机交互 · 计算机科学 2025-10-31 Ned Cooper , Alexandra Zafiroglu

Large Language Models (LLMs), such as Generative Pre-trained Transformers (GPTs) are revolutionizing the generation of human-like text, producing contextually relevant and syntactically correct content. Despite challenges like biases and…

计算与语言 · 计算机科学 2025-08-04 Alper Yaman , Jannik Schwab , Christof Nitsche , Abhirup Sinha , Marco Huber