1 code implementation • 25 Mar 2024 • Kai Mei, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, Yongfeng Zhang
Inspired by these challenges, this paper presents AIOS, an LLM agent operating system, which embeds large language model into operating systems (OS) as the brain of the OS, enabling an operating system "with soul" -- an important step towards AGI.
no code implementations • 20 Feb 2024 • Mingyu Jin, Beichen Wang, Zhaoqian Xue, Suiyuan Zhu, Wenyue Hua, Hua Tang, Kai Mei, Mengnan Du, Yongfeng Zhang
In this study, we introduce "CosmoAgent," an innovative artificial intelligence framework utilizing Large Language Models (LLMs) to simulate complex interactions between human and extraterrestrial civilizations, with a special emphasis on Stephen Hawking's cautionary advice about not sending radio signals haphazardly into the universe.
1 code implementation • 28 Nov 2023 • Wenyue Hua, Lizhou Fan, Lingyao Li, Kai Mei, Jianchao Ji, Yingqiang Ge, Libby Hemphill, Yongfeng Zhang
Can we avoid wars at the crossroads of history?
1 code implementation • 26 Oct 2023 • Kai Mei, Yongfeng Zhang
LightLM tackles the issue by introducing a light-weight deep and narrow Transformer architecture, which is specifically tailored for direct generation of recommendation items.
1 code implementation • 28 May 2023 • Kai Mei, Zheng Li, Zhenting Wang, Yang Zhang, Shiqing Ma
Such attacks can be easily affected by retraining on downstream tasks and with different prompting strategies, limiting the transferability of backdoor attacks.
1 code implementation • NeurIPS 2023 • Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji, Juntao Tan, Shuyuan Xu, Zelong Li, Yongfeng Zhang
This capability is vital for Artificial Intelligence (AI) and should be embedded in comprehensive AI Agents, enabling them to harness expert models for complex task-solving towards Artificial General Intelligence (AGI).
1 code implementation • 5 Apr 2023 • Zhenting Wang, Kai Mei, Juan Zhai, Shiqing Ma
Then, it proposes a unified framework to invert backdoor triggers based on the formalization of triggers and the identified inner behaviors of backdoor models from our analysis.
1 code implementation • 27 Oct 2022 • Zhenting Wang, Kai Mei, Hailun Ding, Juan Zhai, Shiqing Ma
On average, the detection accuracy of our method is 93\%.
no code implementations • 21 Feb 2022 • Jun Liu, Haitao Zhao, Dongtang Ma, Kai Mei, Jibo Wei
In this paper, we aim to quantitatively analyze why DNNs can achieve comparable performance in the physical layer comparing with traditional techniques, and also drive their cost in terms of computational complexity.
no code implementations • 14 Jul 2021 • Kai Mei, Jun Liu, Xiaoying Zhang, Kuo Cao, Nandana Rajatheva, Jibo Wei
Besides, a training data construction approach utilizing least square (LS) estimation results is proposed so that the training data can be collected during the data transmission.
no code implementations • 2 Jun 2021 • Jun Liu, Haitao Zhao, Dongtang Ma, Kai Mei, Jibo Wei
Deep Neural Network (DNN)-based physical layer techniques are attracting considerable interest due to their potential to enhance communication systems.
no code implementations • 17 Jul 2020 • Jun Liu, Kai Mei, Xiaochen Zhang, Des McLernon, Dongtang Ma, Jibo Wei, Syed Ali Raza Zaidi
Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is a key technology component in the evolution towards cognitive radio (CR) in next-generation communication in which the accuracy of timing and frequency synchronization significantly impacts the overall system performance.
no code implementations • 10 Nov 2019 • Kai Mei, Jun Liu, Xiaochen Zhang, Nandana Rajatheva, Jibo Wei
In this situation, our analysis results can be applied to assess the performance and support the design of machine learning-based channel estimation.
no code implementations • 23 Nov 2018 • Jun Liu, Kai Mei, Dongtang Ma, Jibo Wei
This letter illustrates our preliminary works in deep nerual network (DNN) for wireless communication scenario identification in wireless multi-path fading channels.