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08/22/2023
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging
Fast Adversarial Training (FAT) not only improves the model robustness b...
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07/24/2023
COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts
Practical object detection application can lose its effectiveness on ima...
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07/24/2023
Robust Automatic Speech Recognition via WavAugment Guided Phoneme Adversarial Training
Developing a practically-robust automatic speech recognition (ASR) is ch...
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05/29/2023
From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework
Textual adversarial attacks can discover models' weaknesses by adding se...
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05/26/2023
Large Language Models Can be Lazy Learners: Analyze Shortcuts in In-Context Learning
Large language models (LLMs) have recently shown great potential for in-...
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05/20/2023
Joint Generative-Contrastive Representation Learning for Anomalous Sound Detection
In this paper, we propose a joint generative and contrastive representat...
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04/14/2023
FairRec: Fairness Testing for Deep Recommender Systems
Deep learning-based recommender systems (DRSs) are increasingly and wide...
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03/30/2023
ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing
Recent studies have shown that higher accuracy on ImageNet usually leads...
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03/28/2023
TransAudio: Towards the Transferable Adversarial Audio Attack via Learning Contextualized Perturbations
In a transfer-based attack against Automatic Speech Recognition (ASR) sy...
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03/24/2023
PIAT: Parameter Interpolation based Adversarial Training for Image Classification
Adversarial training has been demonstrated to be the most effective appr...
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02/21/2023
Improving Scene Text Image Super-Resolution via Dual Prior Modulation Network
Scene text image super-resolution (STISR) aims to simultaneously increas...
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11/30/2022
Rethinking Out-of-Distribution Detection From a Human-Centric Perspective
Out-Of-Distribution (OOD) detection has received broad attention over th...
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11/29/2022
Context-Aware Robust Fine-Tuning
Contrastive Language-Image Pre-trained (CLIP) models have zero-shot abil...
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11/20/2022
Synthesizing Coherent Story with Auto-Regressive Latent Diffusion Models
Conditioned diffusion models have demonstrated state-of-the-art text-to-...
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10/28/2022
RoChBert: Towards Robust BERT Fine-tuning for Chinese
Despite of the superb performance on a wide range of tasks, pre-trained ...
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10/17/2022
Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation
Capturing emotions within a conversation plays an essential role in mode...
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10/09/2022
Boosting Out-of-distribution Detection with Typical Features
Out-of-distribution (OOD) detection is a critical task for ensuring the ...
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09/16/2022
Enhance the Visual Representation via Discrete Adversarial Training
Adversarial Training (AT), which is commonly accepted as one of the most...
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01/26/2022
An Automated Question-Answering Framework Based on Evolution Algorithm
Building a deep learning model for a Question-Answering (QA) task requir...
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10/15/2021
Adversarial Attacks on ML Defense Models Competition
Due to the vulnerability of deep neural networks (DNNs) to adversarial e...
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07/21/2021
DRDF: Determining the Importance of Different Multimodal Information with Dual-Router Dynamic Framework
In multimodal tasks, we find that the importance of text and image modal...
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07/17/2021
RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition
In fine-grained image recognition (FGIR), the localization and amplifica...
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05/17/2021
Rethinking the Design Principles of Robust Vision Transformer
Recent advances on Vision Transformers (ViT) have shown that self-attent...
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03/04/2021
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
We study the query-based attack against image retrieval to evaluate its ...
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03/02/2021
Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
The remarkable success in face forgery techniques has received considera...
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02/23/2021
Enhancing Model Robustness By Incorporating Adversarial Knowledge Into Semantic Representation
Despite that deep neural networks (DNNs) have achieved enormous success ...
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12/14/2020
The Open Brands Dataset: Unified brand detection and recognition at scale
Intellectual property protection(IPP) have received more and more attent...
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12/10/2020
Composite Adversarial Attacks
Adversarial attack is a technique for deceiving Machine Learning (ML) mo...
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08/14/2020
Landmark detection in Cardiac Magnetic Resonance Imaging Using A Convolutional Neural Network
Purpose: To develop a convolutional neural network (CNN) solution for ro...
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08/11/2020
Sharp Multiple Instance Learning for DeepFake Video Detection
With the rapid development of facial manipulation techniques, face forge...
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07/03/2020
MIRA: Leveraging Multi-Intention Co-click Information in Web-scale Document Retrieval using Deep Neural Networks
We study the problem of deep recall model in industrial web search, whic...
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06/09/2020
GAP++: Learning to generate target-conditioned adversarial examples
Adversarial examples are perturbed inputs which can cause a serious thre...
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05/29/2020
Weakly Supervised Lesion Localization With Probabilistic-CAM Pooling
Localizing thoracic diseases on chest X-ray plays a critical role in cli...
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02/07/2020
Fine-Grained Fashion Similarity Learning by Attribute-Specific Embedding Network
This paper strives to learn fine-grained fashion similarity. In this sim...
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01/06/2020
Deeper Insights into Weight Sharing in Neural Architecture Search
With the success of deep neural networks, Neural Architecture Search (NA...
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12/18/2019
Class Regularization: Improve Few-shot Image Classification by Reducing Meta Shift
Few-shot image classification requires the classifier to robustly cope w...
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11/15/2019
AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients
Deep neural networks have been shown to be vulnerable to adversarial exa...
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11/15/2019
Learning To Characterize Adversarial Subspaces
Deep Neural Networks (DNNs) are known to be vulnerable to the maliciousl...
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11/15/2019
Self-supervised Adversarial Training
Recent work has demonstrated that neural networks are vulnerable to adve...
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11/14/2019
Self-Supervised Learning For Few-Shot Image Classification
Few-shot image classification aims to classify unseen classes with limit...
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11/02/2019
Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning
Recent development of quantitative myocardial blood flow (MBF) mapping a...
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10/16/2019
Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients
Quantification of myocardial perfusion has the potential to improve dete...
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10/10/2019
An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation
Graph Convolutional Network (GCN) has attracted intensive interests rece...
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06/02/2019
Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
High accuracy video label prediction (classification) models are attribu...
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03/18/2019
Bilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks
The task of Language-Based Image Editing (LBIE) aims at generating a tar...
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01/20/2019
