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08/29/2023
Evaluation and Analysis of Hallucination in Large Vision-Language Models
Large Vision-Language Models (LVLMs) have recently achieved remarkable s...
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08/13/2023
Benign Shortcut for Debiasing: Fair Visual Recognition via Intervention with Shortcut Features
Machine learning models often learn to make predictions that rely on sen...
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08/04/2023
You talk what you read: Understanding News Comment Behavior by Dispositional and Situational Attribution
Many news comment mining studies are based on the assumption that commen...
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07/19/2023
CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility
With the rapid evolution of large language models (LLMs), there is a gro...
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07/13/2023
Introducing Foundation Models as Surrogate Models: Advancing Towards More Practical Adversarial Attacks
Recently, the no-box adversarial attack, in which the attacker lacks acc...
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06/06/2023
Towards Alleviating the Object Bias in Prompt Tuning-based Factual Knowledge Extraction
Many works employed prompt tuning methods to automatically optimize prom...
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06/03/2023
Towards Black-box Adversarial Example Detection: A Data Reconstruction-based Method
Adversarial example detection is known to be an effective adversarial de...
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05/06/2023
Echoes: Unsupervised Debiasing via Pseudo-bias Labeling in an Echo Chamber
Neural networks often learn spurious correlations when exposed to biased...
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04/26/2023
From Association to Generation: Text-only Captioning by Unsupervised Cross-modal Mapping
With the development of Vision-Language Pre-training Models (VLPMs) repr...
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04/04/2023
Improved Visual Fine-tuning with Natural Language Supervision
Fine-tuning a pre-trained model can leverage the semantic information fr...
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03/01/2023
Backdoor for Debias: Mitigating Model Bias with Backdoor Attack-based Artificial Bias
With the swift advancement of deep learning, state-of-the-art algorithms...
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12/31/2022
Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples
There is a growing interest in developing unlearnable examples (UEs) aga...
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12/07/2022
Artificial Intelligence Security Competition (AISC)
The security of artificial intelligence (AI) is an important research ar...
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11/14/2022
Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment
CLIP (Contrastive Language-Image Pre-Training) has shown remarkable zero...
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11/02/2022
Fair Visual Recognition via Intervention with Proxy Features
Deep learning models often learn to make predictions that rely on sensit...
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10/26/2022
FairCLIP: Social Bias Elimination based on Attribute Prototype Learning and Representation Neutralization
The Vision-Language Pre-training (VLP) models like CLIP have gained popu...
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07/03/2022
Counterfactually Measuring and Eliminating Social Bias in Vision-Language Pre-training Models
Vision-Language Pre-training (VLP) models have achieved state-of-the-art...
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06/19/2022
JPEG Compression-Resistant Low-Mid Adversarial Perturbation against Unauthorized Face Recognition System
It has been observed that the unauthorized use of face recognition syste...
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06/19/2022
Towards Adversarial Attack on Vision-Language Pre-training Models
While vision-language pre-training model (VLP) has shown revolutionary i...
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05/06/2022
Investigating and Explaining the Frequency Bias in Image Classification
CNNs exhibit many behaviors different from humans, one of which is the c...
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03/10/2022
Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis
Synthesizing pseudo samples is currently the most effective way to solve...
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02/18/2022
Debiasing Backdoor Attack: A Benign Application of Backdoor Attack in Eliminating Data Bias
Backdoor attack is a new AI security risk that has emerged in recent yea...
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11/17/2021
Understanding and Testing Generalization of Deep Networks on Out-of-Distribution Data
Deep network models perform excellently on In-Distribution (ID) data, bu...
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10/18/2021
Learning to Learn a Cold-start Sequential Recommender
The cold-start recommendation is an urgent problem in contemporary onlin...
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10/13/2021
Knowledge Graph-enhanced Sampling for Conversational Recommender System
The traditional recommendation systems mainly use offline user data to t...
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07/26/2021
Benign Adversarial Attack: Tricking Algorithm for Goodness
In spite of the successful application in many fields, machine learning ...
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06/21/2021
Pre-training also Transfers Non-Robustness
Pre-training has enabled many state-of-the-art results on many tasks. In...
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11/19/2020
An Experimental Study of Semantic Continuity for Deep Learning Models
Deep learning models suffer from the problem of semantic discontinuity: ...
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07/27/2020
Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing
Machine learning fairness concerns about the biases towards certain prot...
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07/25/2020
Adversarial Privacy-preserving Filter
While widely adopted in practical applications, face recognition has bee...
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06/18/2020
MMCGAN: Generative Adversarial Network with Explicit Manifold Prior
Generative Adversarial Network(GAN) provides a good generative framework...
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05/25/2020
Adaptive Adversarial Logits Pairing
Adversarial examples provide an opportunity as well as impose a challeng...
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11/28/2019
A Generalization Theory based on Independent and Task-Identically Distributed Assumption
Existing generalization theories analyze the generalization performance ...
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04/22/2019
blessing in disguise: Designing Robust Turing Test by Employing Algorithm Unrobustness
Turing test was originally proposed to examine whether machine's behavio...
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11/24/2018