Search Results for author: Kai Mei

Found 15 papers, 8 papers with code

Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers?

1 code implementation10 Apr 2024 Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang

We employ a probing technique to extract representations from different layers of the model and apply these to classification tasks.

AIOS: LLM Agent Operating System

2 code implementations25 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.

Language Modelling Large Language Model +1

What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents

no code implementations20 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.

Decision Making

LightLM: A Lightweight Deep and Narrow Language Model for Generative Recommendation

1 code implementation26 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.

Hallucination Language Modelling

NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models

1 code implementation28 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.

OpenAGI: When LLM Meets Domain Experts

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).

Benchmarking Natural Language Queries

UNICORN: A Unified Backdoor Trigger Inversion Framework

1 code implementation5 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.

Backdoor Attack

Theoretical Analysis of Deep Neural Networks in Physical Layer Communication

no code implementations21 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.

Intelligent Communication

A Low Complexity Learning-based Channel Estimation for OFDM Systems with Online Training

no code implementations14 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.

BIG-bench Machine Learning

Opening the Black Box of Deep Neural Networks in Physical Layer Communication

no code implementations2 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.

Fine Timing and Frequency Synchronization for MIMO-OFDM: An Extreme Learning Approach

no code implementations17 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.

BIG-bench Machine Learning

Performance Analysis on Machine Learning-Based Channel Estimation

no code implementations10 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.

BIG-bench Machine Learning

Deep Neural Network Aided Scenario Identification in Wireless Multi-path Fading Channels

no code implementations23 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.

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