Search Results for author: Xun Chen

Found 28 papers, 9 papers with code

TrojFST: Embedding Trojans in Few-shot Prompt Tuning

no code implementations16 Dec 2023 Mengxin Zheng, Jiaqi Xue, Xun Chen, Yanshan Wang, Qian Lou, Lei Jiang

We observe the difficulty in constructing a prompt-based backdoor using few-shot prompt-tuning, which involves freezing the PLM and tuning a soft prompt with a restricted set of input samples.

Data Poisoning Language Modelling

Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noise

1 code implementation22 Nov 2023 Yixin Liu, Kaidi Xu, Xun Chen, Lichao Sun

Observing that simply removing the adversarial noise on the training process of the defensive noise can improve the performance of robust unlearnable examples, we identify that solely the surrogate model's robustness contributes to the performance.

Toward Robust Imperceptible Perturbation against Unauthorized Text-to-image Diffusion-based Synthesis

1 code implementation22 Nov 2023 Yixin Liu, Chenrui Fan, Yutong Dai, Xun Chen, Pan Zhou, Lichao Sun

To solve these challenges, we propose MetaCloak, which solves the bi-level poisoning problem with a meta-learning framework with an additional transformation sampling process to craft transferable and robust perturbation.

Bilevel Optimization Denoising +1

Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies

1 code implementation15 Aug 2023 Yilun Liu, Shimin Tao, Weibin Meng, Jingyu Wang, Wenbing Ma, Yanqing Zhao, Yuhang Chen, Hao Yang, Yanfei Jiang, Xun Chen

LogPrompt employs large language models (LLMs) to perform online log analysis tasks via a suite of advanced prompt strategies tailored for log tasks, which enhances LLMs' performance by up to 380. 7% compared with simple prompts.

Anomaly Detection Log Parsing +1

Achieving Covert Communication With A Probabilistic Jamming Strategy

no code implementations8 Aug 2023 Xun Chen, Fujun Gao, Min Qiu, Jia Zhang, Feng Shu, Shihao Yan

In addition, we prove that the minimum jamming power should be the same as Alice's covert transmit power, depending on the covertness and average jamming power constraints.

PanFlowNet: A Flow-Based Deep Network for Pan-sharpening

no code implementations ICCV 2023 Gang Yang, Xiangyong Cao, Wenzhe Xiao, Man Zhou, Aiping Liu, Xun Chen, Deyu Meng

The experimental results verify that the proposed PanFlowNet can generate various HRMS images given an LRMS image and a PAN image.


SSL-Cleanse: Trojan Detection and Mitigation in Self-Supervised Learning

no code implementations16 Mar 2023 Mengxin Zheng, Jiaqi Xue, ZiHao Wang, Xun Chen, Qian Lou, Lei Jiang, XiaoFeng Wang

We evaluated SSL-Cleanse on various datasets using 1200 encoders, achieving an average detection success rate of 82. 2% on ImageNet-100.

Self-Supervised Learning

Memory-adaptive Depth-wise Heterogenous Federated Learning

1 code implementation8 Mar 2023 Kai Zhang, Yutong Dai, Hongyi Wang, Eric Xing, Xun Chen, Lichao Sun

Federated learning is a promising paradigm that allows multiple clients to collaboratively train a model without sharing the local data.

Federated Learning

Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation

1 code implementation NeurIPS 2023 Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler

Specifically, we train an energy-based model on a set of unlabelled protein-ligand complexes using SE(3) denoising score matching and interpret its log-likelihood as binding affinity.

Denoising Drug Discovery

Model-Guided Multi-Contrast Deep Unfolding Network for MRI Super-resolution Reconstruction

1 code implementation15 Sep 2022 Gang Yang, Li Zhang, Man Zhou, Aiping Liu, Xun Chen, Zhiwei Xiong, Feng Wu

Interpretable neural network models are of significant interest since they enhance the trustworthiness required in clinical practice when dealing with medical images.


SOM-Net: Unrolling the Subspace-based Optimization for Solving Full-wave Inverse Scattering Problems

no code implementations8 Sep 2022 Yu Liu, Hao Zhao, Rencheng Song, Xudong Chen, Chang Li, Xun Chen

The final output of the SOM-Net is the full predicted induced current, from which the scattered field and the permittivity image can also be deduced analytically.

Rolling Shutter Correction

EEG-based Emotion Recognition via Efficient Convolutional Neural Network and Contrastive Learning

no code implementations IEEE Sensors Journal 2022 Chang Li, Xuejuan Lin, Yu Liu, Rencheng Song, Juan Cheng, Xun Chen

To achieve a simple and effective model with supervised learning, we propose an efficient CNN and contrastive learning (ECNN-C) method for EEG-based emotion recognition.

Contrastive Learning EEG +2

Fully Automated End-to-End Fake Audio Detection

no code implementations20 Aug 2022 Chenglong Wang, Jiangyan Yi, JianHua Tao, Haiyang Sun, Xun Chen, Zhengkun Tian, Haoxin Ma, Cunhang Fan, Ruibo Fu

The existing fake audio detection systems often rely on expert experience to design the acoustic features or manually design the hyperparameters of the network structure.

Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion

no code implementations14 Jun 2022 Si Chen, Yi Zeng, Jiachen T. Wang, Won Park, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia

Our work is the first to provide a thorough understanding of leveraging model inversion for effective backdoor removal by addressing key questions about reconstructed samples' properties, perceptual similarity, and the potential presence of backdoor triggers.

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation

1 code implementation17 Mar 2022 Kai Zhang, Yu Wang, Hongyi Wang, Lifu Huang, Carl Yang, Xun Chen, Lichao Sun

Furthermore, we propose a Federated learning paradigm with privacy-preserving Relation embedding aggregation (FedR) to tackle the privacy issue in FedE.

Entity Embeddings Federated Learning +4

Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs

no code implementations1 Feb 2022 Hongwei Jin, Xun Chen

Learning the similarity between structured data, especially the graphs, is one of the essential problems.

Graph Learning Privacy Preserving

Toward Open-World Electroencephalogram Decoding Via Deep Learning: A Comprehensive Survey

no code implementations8 Dec 2021 Xun Chen, Chang Li, Aiping Liu, Martin J. McKeown, Ruobing Qian, Z. Jane Wang

Electroencephalogram (EEG) decoding aims to identify the perceptual, semantic, and cognitive content of neural processing based on non-invasively measured brain activity.

EEG Eeg Decoding

Multi-view 3D Reconstruction with Transformer

no code implementations24 Mar 2021 Dan Wang, Xinrui Cui, Xun Chen, Zhengxia Zou, Tianyang Shi, Septimiu Salcudean, Z. Jane Wang, Rabab Ward

Unlike previous CNN-based methods using a separate design, we unify the feature extraction and view fusion in a single Transformer network.

3D Object Reconstruction 3D Reconstruction +1

Multi-View 3D Reconstruction With Transformers

no code implementations ICCV 2021 Dan Wang, Xinrui Cui, Xun Chen, Zhengxia Zou, Tianyang Shi, Septimiu Salcudean, Z. Jane Wang, Rabab Ward

Unlike previous CNN-based methods using a separate design, we unify the feature extraction and view fusion in a single Transformer network.

3D Object Reconstruction 3D Reconstruction +1

Slow Control System for PandaX-III experiment

no code implementations24 Dec 2020 Xiyu Yan, Xun Chen, Yu Chen, Bo Dai, Heng Lin, Tao Li, Ke Han, Kaixiang Ni, Fusang Wang, Shaobo Wang, Qibin Zheng, Xinning Zeng

The PandaX-III experiment uses high pressure gaseous time projection chamber to search for the neutrinoless double beta decay of $^{136}$Xe.

Anomaly Detection High Energy Physics - Experiment Instrumentation and Detectors

MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG

no code implementations17 Aug 2020 Jing Zhang, Deng Liang, Aiping Liu, Min Gao, Xiang Chen, Xu Zhang, Xun Chen

MLBF-Net is composed of three components: 1) multiple lead-specific branches for learning the diversity of multi-lead ECG; 2) cross-lead features fusion by concatenating the output feature maps of all branches for learning the integrity of multi-lead ECG; 3) multi-loss co-optimization for all the individual branches and the concatenated network.

Arrhythmia Detection

LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy

no code implementations31 Jul 2020 Lichao Sun, Jianwei Qian, Xun Chen

In this paper, we proposed a novel design of local differential privacy mechanism for federated learning to address the abovementioned issues.

Federated Learning

A4 : Evading Learning-based Adblockers

no code implementations29 Jan 2020 Shitong Zhu, Zhongjie Wang, Xun Chen, Shasha Li, Umar Iqbal, Zhiyun Qian, Kevin S. Chan, Srikanth V. Krishnamurthy, Zubair Shafiq

Efforts by online ad publishers to circumvent traditional ad blockers towards regaining fiduciary benefits, have been demonstrably successful.


Limits on Axion Couplings from the first 80-day data of PandaX-II Experiment

no code implementations25 Jul 2017 Changbo Fu, Xiaopeng Zhou, Xun Chen, Yunhua Chen, Xiangyi Cui, Deqing Fang, Karl Giboni, Franco Giuliani, Ke Han, Xingtao Huang, Xiangdong Ji, Yonglin Ju, Siao Lei, Shaoli Li, Huaxuan Liu, Jianglai Liu, Yugang Ma, Yajun Mao, Xiangxiang Ren, Andi Tan, Hongwei Wang, Jimin Wang, Meng Wang, Qiuhong Wang, Siguang Wang, Xuming Wang, Zhou Wang, Shiyong Wu, Mengjiao Xiao, Pengwei Xie, Binbin Yan, Yong Yang, Jianfeng Yue, Hongguang Zhang, Tao Zhang, Li Zhao, Ning Zhou

We report new searches for the solar axions and galactic axion-like dark matter particles, using the first low-background data from PandaX-II experiment at China Jinping Underground Laboratory, corresponding to a total exposure of about $2. 7\times 10^4$ kg$\cdot$day.

High Energy Physics - Experiment Solar and Stellar Astrophysics High Energy Physics - Phenomenology

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