Search Results for author: Tianwei Zhang

Found 45 papers, 12 papers with code

ShiftNAS: Towards Automatic Generation of Advanced Mulitplication-Less Neural Networks

no code implementations7 Apr 2022 Xiaoxuan Lou, Guowen Xu, Kangjie Chen, Guanlin Li, Jiwei Li, Tianwei Zhang

Multiplication-less neural networks significantly reduce the time and energy cost on the hardware platform, as the compute-intensive multiplications are replaced with lightweight bit-shift operations.

Neural Architecture Search

$k$NN-NER: Named Entity Recognition with Nearest Neighbor Search

1 code implementation31 Mar 2022 Shuhe Wang, Xiaoya Li, Yuxian Meng, Tianwei Zhang, Rongbin Ouyang, Jiwei Li, Guoyin Wang

Inspired by recent advances in retrieval augmented methods in NLP~\citep{khandelwal2019generalization, khandelwal2020nearest, meng2021gnn}, in this paper, we introduce a $k$ nearest neighbor NER ($k$NN-NER) framework, which augments the distribution of entity labels by assigning $k$ nearest neighbors retrieved from the training set.

Few-Shot Learning Named Entity Recognition +1

Watermarking Pre-trained Encoders in Contrastive Learning

no code implementations20 Jan 2022 Yutong Wu, Han Qiu, Tianwei Zhang, Jiwei L, Meikang Qiu

It is challenging to migrate existing watermarking techniques from the classification tasks to the contrastive learning scenario, as the owner of the encoder lacks the knowledge of the downstream tasks which will be developed from the encoder in the future.

Contrastive Learning

Faster Nearest Neighbor Machine Translation

no code implementations15 Dec 2021 Shuhe Wang, Jiwei Li, Yuxian Meng, Rongbin Ouyang, Guoyin Wang, Xiaoya Li, Tianwei Zhang, Shi Zong

The core idea of Faster $k$NN-MT is to use a hierarchical clustering strategy to approximate the distance between the query and a data point in the datastore, which is decomposed into two parts: the distance between the query and the center of the cluster that the data point belongs to, and the distance between the data point and the cluster center.

Machine Translation Translation

A General Framework for Defending Against Backdoor Attacks via Influence Graph

no code implementations29 Nov 2021 Xiaofei Sun, Jiwei Li, Xiaoya Li, Ziyao Wang, Tianwei Zhang, Han Qiu, Fei Wu, Chun Fan

In this work, we propose a new and general framework to defend against backdoor attacks, inspired by the fact that attack triggers usually follow a \textsc{specific} type of attacking pattern, and therefore, poisoned training examples have greater impacts on each other during training.

Triggerless Backdoor Attack for NLP Tasks with Clean Labels

1 code implementation15 Nov 2021 Leilei Gan, Jiwei Li, Tianwei Zhang, Xiaoya Li, Yuxian Meng, Fei Wu, Yi Yang, Shangwei Guo, Chun Fan

To deal with this issue, in this paper, we propose a new strategy to perform textual backdoor attacks which do not require an external trigger, and the poisoned samples are correctly labeled.

Backdoor Attack

Interpreting Deep Learning Models in Natural Language Processing: A Review

no code implementations20 Oct 2021 Xiaofei Sun, Diyi Yang, Xiaoya Li, Tianwei Zhang, Yuxian Meng, Han Qiu, Guoyin Wang, Eduard Hovy, Jiwei Li

Neural network models have achieved state-of-the-art performances in a wide range of natural language processing (NLP) tasks.

GNN-LM: Language Modeling based on Global Contexts via GNN

1 code implementation ICLR 2022 Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li

Inspired by the notion that ``{\it to copy is easier than to memorize}``, in this work, we introduce GNN-LM, which extends the vanilla neural language model (LM) by allowing to reference similar contexts in the entire training corpus.

Language Modelling

Fingerprinting Multi-exit Deep Neural Network Models via Inference Time

no code implementations7 Oct 2021 Tian Dong, Han Qiu, Tianwei Zhang, Jiwei Li, Hewu Li, Jialiang Lu

Specifically, we design an effective method to generate a set of fingerprint samples to craft the inference process with a unique and robust inference time cost as the evidence for model ownership.

BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models

no code implementations ICLR 2022 Kangjie Chen, Yuxian Meng, Xiaofei Sun, Shangwei Guo, Tianwei Zhang, Jiwei Li, Chun Fan

The key feature of our attack is that the adversary does not need prior information about the downstream tasks when implanting the backdoor to the pre-trained model.

Backdoor Attack Transfer Learning

NASPY: Automated Extraction of Automated Machine Learning Models

no code implementations ICLR 2022 Xiaoxuan Lou, Shangwei Guo, Jiwei Li, Yaoxin Wu, Tianwei Zhang

We present NASPY, an end-to-end adversarial framework to extract the networkarchitecture of deep learning models from Neural Architecture Search (NAS).

Model extraction Neural Architecture Search

A Novel Watermarking Framework for Ownership Verification of DNN Architectures

no code implementations29 Sep 2021 Xiaoxuan Lou, Shangwei Guo, Tianwei Zhang, Jiwei Li, Yinqian Zhang, Yang Liu

We present a novel watermarking scheme to achieve the intellectual property (IP) protection and ownership verification of DNN architectures.

Model extraction Neural Architecture Search

Towards Robust Point Cloud Models with Context-Consistency Network and Adaptive Augmentation

no code implementations29 Sep 2021 Guanlin Li, Guowen Xu, Han Qiu, Ruan He, Jiwei Li, Tianwei Zhang

Extensive evaluations indicate the integration of the two techniques provides much more robustness than existing defense solutions for 3D models.

Data Augmentation

Practical and Private Heterogeneous Federated Learning

no code implementations29 Sep 2021 Hanxiao Chen, Meng Hao, Hongwei Li, Guangxiao Niu, Guowen Xu, Huawei Wang, Yuan Zhang, Tianwei Zhang

Heterogeneous federated learning (HFL) enables clients with different computation/communication capabilities to collaboratively train their own customized models, in which the knowledge of models is shared via clients' predictions on a public dataset.

Federated Learning

Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters

1 code implementation3 Sep 2021 Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang

Modern GPU datacenters are critical for delivering Deep Learning (DL) models and services in both the research community and industry.

$k$Folden: $k$-Fold Ensemble for Out-Of-Distribution Detection

1 code implementation29 Aug 2021 Xiaoya Li, Jiwei Li, Xiaofei Sun, Chun Fan, Tianwei Zhang, Fei Wu, Yuxian Meng, Jun Zhang

For a task with $k$ training labels, $k$Folden induces $k$ sub-models, each of which is trained on a subset with $k-1$ categories with the left category masked unknown to the sub-model.

Classification OOD Detection +2

AcousticFusion: Fusing Sound Source Localization to Visual SLAM in Dynamic Environments

no code implementations3 Aug 2021 Tianwei Zhang, Huayan Zhang, Xiaofei Li, Junfeng Chen, Tin Lun Lam, Sethu Vijayakumar

Dynamic objects in the environment, such as people and other agents, lead to challenges for existing simultaneous localization and mapping (SLAM) approaches.

Depth Estimation Simultaneous Localization and Mapping

PoseFusion2: Simultaneous Background Reconstruction and Human Shape Recovery in Real-time

no code implementations2 Aug 2021 Huayan Zhang, Tianwei Zhang, Tin Lun Lam, Sethu Vijayakumar

Dynamic environments that include unstructured moving objects pose a hard problem for Simultaneous Localization and Mapping (SLAM) performance.

Pose Estimation Simultaneous Localization and Mapping

A Novel Verifiable Fingerprinting Scheme for Generative Adversarial Networks

no code implementations19 Jun 2021 Guanlin Li, Guowen Xu, Han Qiu, Shangwei Guo, Run Wang, Jiwei Li, Tianwei Zhang

Our scheme constructs a composite deep learning model from the target GAN and a classifier.

Defending against Backdoor Attacks in Natural Language Generation

1 code implementation3 Jun 2021 Chun Fan, Xiaoya Li, Yuxian Meng, Xiaofei Sun, Xiang Ao, Fei Wu, Jiwei Li, Tianwei Zhang

To defend against these attacks, we propose to detect the attack trigger by examining the effect of deleting or replacing certain words on the generation outputs, which we find successful for certain types of attacks.

Backdoor Attack Dialogue Generation +2

Modeling Text-visual Mutual Dependency for Multi-modal Dialog Generation

1 code implementation30 May 2021 Shuhe Wang, Yuxian Meng, Xiaofei Sun, Fei Wu, Rongbin Ouyang, Rui Yan, Tianwei Zhang, Jiwei Li

Specifically, we propose to model the mutual dependency between text-visual features, where the model not only needs to learn the probability of generating the next dialog utterance given preceding dialog utterances and visual contexts, but also the probability of predicting the visual features in which a dialog utterance takes place, leading the generated dialog utterance specific to the visual context.

Fast Nearest Neighbor Machine Translation

1 code implementation Findings (ACL) 2022 Yuxian Meng, Xiaoya Li, Xiayu Zheng, Fei Wu, Xiaofei Sun, Tianwei Zhang, Jiwei Li

Fast $k$NN-MT constructs a significantly smaller datastore for the nearest neighbor search: for each word in a source sentence, Fast $k$NN-MT first selects its nearest token-level neighbors, which is limited to tokens that are the same as the query token.

Machine Translation Translation

Parameter Estimation for the SEIR Model Using Recurrent Nets

no code implementations30 May 2021 Chun Fan, Yuxian Meng, Xiaofei Sun, Fei Wu, Tianwei Zhang, Jiwei Li

Next, based on this recurrent net that is able to generalize SEIR simulations, we are able to transform the objective to a differentiable one with respect to $\Theta_\text{SEIR}$, and straightforwardly obtain its optimal value.

Sentence Similarity Based on Contexts

no code implementations17 May 2021 Xiaofei Sun, Yuxian Meng, Xiang Ao, Fei Wu, Tianwei Zhang, Jiwei Li, Chun Fan

The proposed framework is based on the core idea that the meaning of a sentence should be defined by its contexts, and that sentence similarity can be measured by comparing the probabilities of generating two sentences given the same context.

Language Modelling Semantic Similarity +2

A search for cloud cores affected by shocked carbon chain chemistry in L1251

no code implementations11 Mar 2021 Xunchuan Liu, Y. Wu, C. Zhang, X. Chen, L. -H. Lin, S. -L. Qin, T. Liu, C. Henkel, J. Wang, H. -L. Liu, J. Yuan, L. -X. Yuan, J. Li, Z. -Q. Shen, D. Li, J. Esimbek, K. Wang, L. -X. Li, Kee-Tae Kim, L. Zhu, D. Madones, N. Inostroza, F. -Y. Meng, Tianwei Zhang, K. Tatematsu, Y. Xu, B. -G. Ju, A. Kraus, F. -W. Xu

The signposts of ongoing SCCC and the broadened line widths of C$_3$S and C$_4$H in L1251-1 as well as the distribution of HC$_3$N are also related to outflow activities in this region.

Astrophysics of Galaxies Solar and Stellar Astrophysics

Local Black-box Adversarial Attacks: A Query Efficient Approach

no code implementations4 Jan 2021 Tao Xiang, Hangcheng Liu, Shangwei Guo, Tianwei Zhang, Xiaofeng Liao

Based on this property, we identify the discriminative areas of a given clean example easily for local perturbations.

DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

no code implementations13 Dec 2020 Han Qiu, Yi Zeng, Shangwei Guo, Tianwei Zhang, Meikang Qiu, Bhavani Thuraisingham

In this paper, we investigate the effectiveness of data augmentation techniques in mitigating backdoor attacks and enhancing DL models' robustness.

Backdoor Attack Data Augmentation

FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques

1 code implementation3 Dec 2020 Han Qiu, Yi Zeng, Tianwei Zhang, Yong Jiang, Meikang Qiu

With more and more advanced adversarial attack methods have been developed, a quantity of corresponding defense solutions were designed to enhance the robustness of DNN models.

Adversarial Attack Data Augmentation

Privacy-preserving Collaborative Learning with Automatic Transformation Search

2 code implementations CVPR 2021 Wei Gao, Shangwei Guo, Tianwei Zhang, Han Qiu, Yonggang Wen, Yang Liu

Comprehensive evaluations demonstrate that the policies discovered by our method can defeat existing reconstruction attacks in collaborative learning, with high efficiency and negligible impact on the model performance.

Data Augmentation

RigidFusion: Robot Localisation and Mapping in Environments with Large Dynamic Rigid Objects

no code implementations21 Oct 2020 Ran Long, Christian Rauch, Tianwei Zhang, Vladimir Ivan, Sethu Vijayakumar

Here, we propose to treat all dynamic parts as one rigid body and simultaneously segment and track both static and dynamic components.


SplitFusion: Simultaneous Tracking and Mapping for Non-Rigid Scenes

no code implementations4 Jul 2020 Yang Li, Tianwei Zhang, Yoshihiko Nakamura, Tatsuya Harada

We present SplitFusion, a novel dense RGB-D SLAM framework that simultaneously performs tracking and dense reconstruction for both rigid and non-rigid components of the scene.

A Unified Framework for Analyzing and Detecting Malicious Examples of DNN Models

1 code implementation26 Jun 2020 Kaidi Jin, Tianwei Zhang, Chao Shen, Yufei Chen, Ming Fan, Chenhao Lin, Ting Liu

In this paper, we present a unified framework for detecting malicious examples and protecting the inference results of Deep Learning models.

Adversarial Defense

Topology-aware Differential Privacy for Decentralized Image Classification

no code implementations14 Jun 2020 Shangwei Guo, Tianwei Zhang, Guowen Xu, Han Yu, Tao Xiang, Yang Liu

In this paper, we design Top-DP, a novel solution to optimize the differential privacy protection of decentralized image classification systems.

Classification Image Classification

Stealing Deep Reinforcement Learning Models for Fun and Profit

no code implementations9 Jun 2020 Kangjie Chen, Shangwei Guo, Tianwei Zhang, Xiaofei Xie, Yang Liu

This paper presents the first model extraction attack against Deep Reinforcement Learning (DRL), which enables an external adversary to precisely recover a black-box DRL model only from its interaction with the environment.

Decision Making Imitation Learning +2

Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques

1 code implementation27 May 2020 Han Qiu, Yi Zeng, Qinkai Zheng, Tianwei Zhang, Meikang Qiu, Gerard Memmi

Extensive evaluations indicate that our solutions can effectively mitigate all existing standard and advanced attack techniques, and beat 11 state-of-the-art defense solutions published in top-tier conferences over the past 2 years.

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

no code implementations14 May 2020 Jianwen Sun, Tianwei Zhang, Xiaofei Xie, Lei Ma, Yan Zheng, Kangjie Chen, Yang Liu

Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed.

Adversarial Attack reinforcement-learning

Learning to Optimize Non-Rigid Tracking

no code implementations CVPR 2020 Yang Li, Aljaž Božič, Tianwei Zhang, Yanli Ji, Tatsuya Harada, Matthias Nießner

One of the widespread solutions for non-rigid tracking has a nested-loop structure: with Gauss-Newton to minimize a tracking objective in the outer loop, and Preconditioned Conjugate Gradient (PCG) to solve a sparse linear system in the inner loop.

FlowFusion: Dynamic Dense RGB-D SLAM Based on Optical Flow

no code implementations11 Mar 2020 Tianwei Zhang, Huayan Zhang, Yang Li, Yoshihiko Nakamura, Lei Zhang

Dynamic environments are challenging for visual SLAM since the moving objects occlude the static environment features and lead to wrong camera motion estimation.

Motion Estimation Optical Flow Estimation

Byzantine-resilient Decentralized Stochastic Gradient Descent

no code implementations20 Feb 2020 Shangwei Guo, Tianwei Zhang, Han Yu, Xiaofei Xie, Lei Ma, Tao Xiang, Yang Liu

It guarantees that each benign node in a decentralized system can train a correct model under very strong Byzantine attacks with an arbitrary number of faulty nodes.

Edge-computing Image Classification

VerIDeep: Verifying Integrity of Deep Neural Networks through Sensitive-Sample Fingerprinting

no code implementations9 Aug 2018 Zecheng He, Tianwei Zhang, Ruby B. Lee

Even small weight changes can be clearly reflected in the model outputs, and observed by the customer.

Privacy-preserving Machine Learning through Data Obfuscation

no code implementations5 Jul 2018 Tianwei Zhang, Zecheng He, Ruby B. Lee

While it is prevalent to outsource model training and serving tasks in the cloud, it is important to protect the privacy of sensitive samples in the training dataset and prevent information leakage to untrusted third parties.

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