Search Results for author: Shun Zhang

Found 35 papers, 4 papers with code

Towards Real-world Scenario: Imbalanced New Intent Discovery

no code implementations5 Jun 2024 Shun Zhang, Chaoran Yan, Jian Yang, Jiaheng Liu, Ying Mo, Jiaqi Bai, Tongliang Li, Zhoujun Li

New Intent Discovery (NID) aims at detecting known and previously undefined categories of user intent by utilizing limited labeled and massive unlabeled data.

Intent Discovery Representation Learning

RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations

no code implementations13 Apr 2024 Shun Zhang, Chaoran Yan, Jian Yang, Changyu Ren, Jiaqi Bai, Tongliang Li, Zhoujun Li

To address the aforementioned challenges, we propose a Robust New Intent Discovery (RoNID) framework optimized by an EM-style method, which focuses on constructing reliable pseudo-labels and obtaining cluster-friendly discriminative representations.

Contrastive Learning Intent Discovery +2

New Intent Discovery with Attracting and Dispersing Prototype

no code implementations25 Mar 2024 Shun Zhang, Jian Yang, Jiaqi Bai, Chaoran Yan, Tongliang Li, Zhao Yan, Zhoujun Li

New Intent Discovery (NID) aims to recognize known and infer new intent categories with the help of limited labeled and large-scale unlabeled data.

Intent Discovery Language Modelling +1

STAR-RIS Aided Integrated Sensing and Communication over High Mobility Scenario

no code implementations18 Mar 2024 Muye Li, Shun Zhang, Yao Ge, Zan Li, Feifei Gao, Pingzhi Fan

With the help of sensing results, the phase shifts of the STAR-RIS are delicately designed, which can significantly improve the received signal strength for both the RSUs and the in-vehicle UE, and can finally enhance the sensing and communication performance.

C-ICL: Contrastive In-context Learning for Information Extraction

no code implementations17 Feb 2024 Ying Mo, Jiahao Liu, Jian Yang, Qifan Wang, Shun Zhang, Jingang Wang, Zhoujun Li

There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related to named entity recognition (NER) and relation extraction (RE).

In-Context Learning Miscellaneous +4

Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble

no code implementations30 Jan 2024 Shun Zhang, Zhenfang Chen, Sunli Chen, Yikang Shen, Zhiqing Sun, Chuang Gan

Reinforcement Learning from Human Feedback (RLHF) is a widely adopted approach for aligning large language models with human values.

Language Modelling Large Language Model +1

Multi-Task Learning for Front-End Text Processing in TTS

1 code implementation12 Jan 2024 Wonjune Kang, Yun Wang, Shun Zhang, Arthur Hinsvark, Qing He

We propose a multi-task learning (MTL) model for jointly performing three tasks that are commonly solved in a text-to-speech (TTS) front-end: text normalization (TN), part-of-speech (POS) tagging, and homograph disambiguation (HD).

Language Modelling Multi-Task Learning +3

Beam Squint Assisted User Localization in Near-Field Integrated Sensing and Communications Systems

no code implementations25 Sep 2023 Hongliang Luo, Feifei Gao, Wanmai Yuan, Shun Zhang

In this paper, we find that with the aid of true-time-delay lines (TTDs), the range and trajectory of the beam squint in near-field communications systems can be freely controlled, and hence it is possible to reversely utilize the beam squint for user localization.

M$^3$CS: Multi-Target Masked Point Modeling with Learnable Codebook and Siamese Decoders

no code implementations23 Sep 2023 Qibo Qiu, Honghui Yang, Wenxiao Wang, Shun Zhang, Haiming Gao, Haochao Ying, Wei Hua, Xiaofei He

Specifically, with masked point cloud as input, M$^3$CS introduces two decoders to predict masked representations and the original points simultaneously.

Decoder Diversity

Policy Expectation Counts? The Impact of China's Delayed Retirement Announcement on Urban Households Savings Rates

no code implementations5 Jul 2023 Shun Zhang

This article examines the impact of China's delayed retirement announcement on households' savings behavior using data from China Family Panel Studies (CFPS).

Two-Bit RIS-Aided Communications at 3.5GHz: Some Insights from the Measurement Results Under Multiple Practical Scenes

no code implementations19 May 2023 Shun Zhang, Haoran Sun, Runze Yu, Hongshenyuan Cui, Jian Ren, Feifei Gao, Shi Jin, Hongxiang Xie, Hao Wang

In particular, we adopt a self-developed broadband intelligent communication system 40MHz-Net (BICT-40N) terminal in order to fully acquire the channel information.

Intelligent Communication Quantization

Hyper-Decision Transformer for Efficient Online Policy Adaptation

no code implementations17 Apr 2023 Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, Chuang Gan

To address this challenge, we propose a new framework, called Hyper-Decision Transformer (HDT), that can generalize to novel tasks from a handful of demonstrations in a data- and parameter-efficient manner.

Planning with Large Language Models for Code Generation

no code implementations9 Mar 2023 Shun Zhang, Zhenfang Chen, Yikang Shen, Mingyu Ding, Joshua B. Tenenbaum, Chuang Gan

Existing large language model-based code generation pipelines typically use beam search or sampling algorithms during the decoding process.

Code Generation Language Modelling +1

Benchmarking Adversarial Patch Against Aerial Detection

1 code implementation30 Oct 2022 Jiawei Lian, Shaohui Mei, Shun Zhang, Mingyang Ma

DNNs are vulnerable to adversarial examples, which poses great security concerns for security-critical systems.

Benchmarking

KG-MTT-BERT: Knowledge Graph Enhanced BERT for Multi-Type Medical Text Classification

no code implementations8 Oct 2022 Yong He, Cheng Wang, Shun Zhang, Nan Li, Zhaorong Li, Zhenyu Zeng

Herein, we develop a new model called KG-MTT-BERT (Knowledge Graph Enhanced Multi-Type Text BERT) by extending the BERT model for long and multi-type text with the integration of the medical knowledge graph.

Question Answering text-classification +1

Computer Vision-Aided Reconfigurable Intelligent Surface-Based Beam Tracking: Prototyping and Experimental Results

no code implementations11 Jul 2022 Ming Ouyang, Yucong Wang, Feifei Gao, Shun Zhang, Puchu Li, Jian Ren

The vision-aided RIS prototype system is tested in two mobile scenarios: RIS works in near-field conditions as a passive array antenna of the base station; RIS works in far-field conditions to assist the communication between the base station and the user equipment.

Reconfigurable Intelligent Surface for Near Field Communications: Beamforming and Sensing

no code implementations21 Apr 2022 Yuhua Jiang, Feifei Gao, Mengnan Jian, Shun Zhang, Wei zhang

However, the conventional continuous aperture RIS is designed to convert the incoming planar waves into the outgoing planar waves, which is not the optimal reflecting scheme when the receiver is not a planar array and is located in the near field of the RIS.

Deep Learning-based Time-varying Channel Estimation for RIS Assisted Communication

no code implementations12 Aug 2021 Meng Xu, Shun Zhang, Jianpeng Ma, Octavia A. Dobre

Reconfigurable intelligent surface (RIS) is considered as a revolutionary technology for future wireless communication networks.

Time Series Time Series Analysis

Deep Learning Based Antenna-time Domain Channel Extrapolation for Hybrid mmWave Massive MIMO

no code implementations9 Aug 2021 Shunbo Zhang, Shun Zhang, Jianpeng Ma, Tian Liu, Octavia A. Dobre

We design a latent ordinary differential equation (ODE)-based network under the variational auto-encoder (VAE) framework to learn the mapping function from the partial uplink channels to the full downlink ones at the BS side.

Decoder

Cascaded Channel Estimation for RIS Assisted mmWave MIMO Transmissions

no code implementations19 Jun 2021 Yushan Liu, Shun Zhang, Feifei Gao, Jie Tang, Octavia A. Dobre

Channel estimation is challenging for the reconfigurable intelligence surface (RIS) assisted millimeter wave (mmWave) communications.

AIRIS: Artificial Intelligence Enhanced Signal Processing in Reconfigurable Intelligent Surface Communications

no code implementations1 Jun 2021 Shun Zhang, Muye Li, Mengnan Jian, Yajun Zhao, Feifei Gao

Reconfigurable intelligent surface (RIS) is an emerging meta-surface that can provide additional communications links through reflecting the signals, and has been recognized as a strong candidate of 6G mobile communications systems.

Scheduling

Deep Learning Based RIS Channel Extrapolation with Element-grouping

no code implementations14 May 2021 Shunbo Zhang, Shun Zhang, Feifei Gao, Jianpeng Ma, Octavia A. Dobre

Reconfigurable intelligent surface (RIS) is considered as a revolutionary technology for future wireless communication networks.

Deep Learning based Channel Extrapolation for Large-Scale Antenna Systems: Opportunities, Challenges and Solutions

no code implementations25 Feb 2021 Shun Zhang, Yushan Liu, Feifei Gao, Chengwen Xing, Jianping An, Octavia A. Dobre

With the depletion of spectrum, wireless communication systems turn to exploit large antenna arrays to achieve the degree of freedom in space domain, such as millimeter wave massive multi-input multioutput (MIMO), reconfigurable intelligent surface assisted communications and cell-free massive MIMO.

Information Theory Signal Processing Information Theory

Deep Learning based Antenna Selection and CSI Extrapolation in Massive MIMO Systems

no code implementations18 Jan 2021 Bo Lin, Feifei Gao, Shun Zhang, Ting Zhou, Ahmed Alkhateeb

A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge training overhead caused by downlink transmission, like channel estimation, downlink beamforming and covariance observation.

Combinatorial Optimization

Ordinary Differential Equation-based CNN for Channel Extrapolation over RIS-assisted Communication

no code implementations22 Dec 2020 Meng Xu, Shun Zhang, Caijun Zhong, Jianpeng Ma, Octavia A. Dobre

The reconfigurable intelligent surface (RIS) is considered as a promising new technology for reconfiguring wireless communication environments.

Information Theory Information Theory

Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO

no code implementations3 Sep 2020 Yindi Yang, Shun Zhang, Feifei Gao, Chao Xu, Jianpeng Ma, Octavia A. Dobre

In massive multiple-input multiple-output (MIMO) systems, the large number of antennas would bring a great challenge for the acquisition of the accurate channel state information, especially in the frequency division duplex mode.

$S^{2}$-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning

no code implementations24 Apr 2019 Yanwei Fu, Donghao Li, Xinwei Sun, Shun Zhang, Yizhou Wang, Yuan YAO

This paper proposes a novel Stochastic Split Linearized Bregman Iteration ($S^{2}$-LBI) algorithm to efficiently train the deep network.

Computational Efficiency Model Selection

Probabilistic Matrix Factorization with Personalized Differential Privacy

no code implementations19 Oct 2018 Shun Zhang, Laixiang Liu, Zhili Chen, Hong Zhong

The results show that the PDP-PMF scheme performs well on protecting the privacy of each user and its recommendation quality is much better than the DP-PMF scheme.

Recommendation Systems

Extreme Network Compression via Filter Group Approximation

no code implementations ECCV 2018 Bo Peng, Wenming Tan, Zheyang Li, Shun Zhang, Di Xie, ShiLiang Pu

In this paper we propose a novel decomposition method based on filter group approximation, which can significantly reduce the redundancy of deep convolutional neural networks (CNNs) while maintaining the majority of feature representation.

General Classification Image Classification

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

2 code implementations5 Oct 2017 Shun Zhang, Jia-Bin Huang, Jongwoo Lim, Yihong Gong, Jinjun Wang, Narendra Ahuja, Ming-Hsuan Yang

Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often appear drastically different in multiple shots due to significant variations in scale, pose, expression, illumination, and make-up.

Clustering

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