b'Hang Su'

research

∙ 09/21/2023

How Robust is Google's Bard to Adversarial Image Attacks?

Multimodal Large Language Models (MLLMs) that integrate text and other m...

0 Yinpeng Dong, et al. ∙

research

∙ 08/29/2023

Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence

Continual learning aims to empower artificial intelligence (AI) with str...

0 Liyuan Wang, et al. ∙

research

∙ 08/09/2023

A Unified Interactive Model Evaluation for Classification, Object Detection, and Instance Segmentation in Computer Vision

Existing model evaluation tools mainly focus on evaluating classificatio...

0 Changjian Chen, et al. ∙

research

∙ 08/04/2023

AdvFAS: A robust face anti-spoofing framework against adversarial examples

Ensuring the reliability of face recognition systems against presentatio...

0 Jiawei Chen, et al. ∙

research

∙ 07/24/2023

COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts

Practical object detection application can lose its effectiveness on ima...

0 Xiaofeng Mao, et al. ∙

research

∙ 07/21/2023

Improving Viewpoint Robustness for Visual Recognition via Adversarial Training

Viewpoint invariance remains challenging for visual recognition in the 3...

0 Shouwei Ruan, et al. ∙

research

∙ 06/28/2023

Distributional Modeling for Location-Aware Adversarial Patches

Adversarial patch is one of the important forms of performing adversaria...

0 Xingxing Wei, et al. ∙

research

∙ 06/15/2023

DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks in the Physical World

Adversarial attacks in the physical world, particularly patch attacks, p...

0 Caixin Kang, et al. ∙

research

∙ 06/15/2023

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

While significant progress has been made on Physics-Informed Neural Netw...

1 Zhongkai Hao, et al. ∙

research

∙ 06/05/2023

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks

Physics-informed Neural Networks (PINNs) have recently achieved remarkab...

0 Jiachen Yao, et al. ∙

research

∙ 05/30/2023

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data

The neural operator has emerged as a powerful tool in learning mappings ...

0 Songming Liu, et al. ∙

research

∙ 05/25/2023

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

Score distillation sampling (SDS) has shown great promise in text-to-3D ...

0 Zhengyi Wang, et al. ∙

research

∙ 05/24/2023

Robust Classification via a Single Diffusion Model

Recently, diffusion models have been successfully applied to improving a...

0 Huanran Chen, et al. ∙

research

∙ 05/23/2023

DIVA: A Dirichlet Process Based Incremental Deep Clustering Algorithm via Variational Auto-Encoder

Generative model-based deep clustering frameworks excel in classifying c...

0 Zhenshan Bing, et al. ∙

research

∙ 05/15/2023

Using LLM-assisted Annotation for Corpus Linguistics: A Case Study of Local Grammar Analysis

Chatbots based on Large Language Models (LLMs) have shown strong capabil...

0 Danni Yu, et al. ∙

research

∙ 05/13/2023

Decision-based iterative fragile watermarking for model integrity verification

Typically, foundation models are hosted on cloud servers to meet the hig...

0 Zhaoxia Yin, et al. ∙

research

∙ 05/08/2023

Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization

Deep Neural Networks (DNNs) have recently made significant progress in m...

0 Zhaoxia Yin, et al. ∙

research

∙ 05/07/2023

Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning

With the help of conditioning mechanisms, the state-of-the-art diffusion...

0 Shengfang Zhai, et al. ∙

research

∙ 04/29/2023

Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning

Meta-reinforcement learning enables artificial agents to learn from rela...

0 Mingyang Wang, et al. ∙

research

∙ 04/25/2023

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning

Guided sampling is a vital approach for applying diffusion models in rea...

0 Cheng Lu, et al. ∙

research

∙ 03/31/2023

A Closer Look at Parameter-Efficient Tuning in Diffusion Models

Large-scale diffusion models like Stable Diffusion are powerful and find...

0 Chendong Xiang, et al. ∙

research

∙ 03/28/2023

Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition

Face recognition is a prevailing authentication solution in numerous bio...

0 Xiao Yang, et al. ∙

research

∙ 03/20/2023

Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving

3D object detection is an important task in autonomous driving to percei...

0 Yinpeng Dong, et al. ∙

research

∙ 03/12/2023

One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale

This paper proposes a unified diffusion framework (dubbed UniDiffuser) t...

0 Fan Bao, et al. ∙

research

∙ 03/09/2023

Reward Informed Dreamer for Task Generalization in Reinforcement Learning

A long-standing goal of reinforcement learning is that algorithms can le...

0 Chengyang Ying, et al. ∙

research

∙ 02/28/2023

GNOT: A General Neural Operator Transformer for Operator Learning

Learning partial differential equations' (PDEs) solution operators is an...

0 Zhongkai Hao, et al. ∙

research

∙ 01/31/2023

A Comprehensive Survey of Continual Learning: Theory, Method and Application

To cope with real-world dynamics, an intelligent agent needs to incremen...

0 Liyuan Wang, et al. ∙

research

∙ 01/29/2023

Learning Analytics from Spoken Discussion Dialogs in Flipped Classroom

The flipped classroom is a new pedagogical strategy that has been gainin...

0 Hang Su, et al. ∙

research

∙ 11/15/2022

Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications

Recent advances of data-driven machine learning have revolutionized fiel...

0 Zhongkai Hao, et al. ∙

research

∙ 11/02/2022

Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network

Model-based reinforcement learning usually suffers from a high sample co...

0 Yao Feng, et al. ∙

research

∙ 10/25/2022

Dynamic Speech Endpoint Detection with Regression Targets

Interactive voice assistants have been widely used as input interfaces i...

0 Dawei Liang, et al. ∙

research

∙ 10/08/2022

ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints

Recent studies have demonstrated that visual recognition models lack rob...

0 Yinpeng Dong, et al. ∙

research

∙ 10/06/2022

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs

We present a unified hard-constraint framework for solving geometrically...

0 Songming Liu, et al. ∙

research

∙ 09/29/2022

Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling

In offline reinforcement learning, weighted regression is a common metho...

0 Huayu Chen, et al. ∙

research

∙ 09/15/2022

Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients

Deep learning based approaches like Physics-informed neural networks (PI...

15 Zhongkai Hao, et al. ∙

research

∙ 09/15/2022

On the Reuse Bias in Off-Policy Reinforcement Learning

Importance sampling (IS) is a popular technique in off-policy evaluation...

0 Chengyang Ying, et al. ∙

research

∙ 06/12/2022

Consistent Attack: Universal Adversarial Perturbation on Embodied Vision Navigation

Embodied agents in vision navigation coupled with deep neural networks h...

0 You Qiaoben, et al. ∙

research

∙ 06/09/2022

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Though deep reinforcement learning (DRL) has obtained substantial succes...

0 Chengyang Ying, et al. ∙

research

∙ 06/09/2022

GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing

Certified defenses such as randomized smoothing have shown promise towar...

0 Zhongkai Hao, et al. ∙

research

∙ 04/23/2022

Human-Robot Shared Control for Surgical Robot Based on Context-Aware Sim-to-Real Adaptation

Human-robot shared control, which integrates the advantages of both huma...

0 Dandan Zhang, et al. ∙

research

∙ 03/13/2022

Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model

In high-stake scenarios like medical treatment and auto-piloting, it's r...

2 Jialian Li, et al. ∙

research

∙ 03/13/2022

Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based Prior

Adversarial attacks have been extensively studied in recent years since ...

0 Yinpeng Dong, et al. ∙

research

∙ 03/09/2022

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition

Recent studies have revealed the vulnerability of face recognition model...

0 Xiao Yang, et al. ∙

research

∙ 11/21/2021

Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks

Despite its great success, deep learning severely suffers from robustnes...

0 Kaiyuan Liu, et al. ∙

research

∙ 10/15/2021

Adversarial Attacks on ML Defense Models Competition

Due to the vulnerability of deep neural networks (DNNs) to adversarial e...

0 Yinpeng Dong, et al. ∙

research

∙ 10/13/2021

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness

The vulnerability of deep neural networks to adversarial examples has mo...

0 Xiao Yang, et al. ∙

research

∙ 09/30/2021

You Cannot Easily Catch Me: A Low-Detectable Adversarial Patch for Object Detectors

Blind spots or outright deceit can bedevil and deceive machine learning ...

1 Zijian Zhu, et al. ∙

research

∙ 09/27/2021

Query-based Adversarial Attacks on Graph with Fake Nodes

While deep neural networks have achieved great success on the graph anal...

0 Zhengyi Wang, et al. ∙

research

∙ 09/13/2021

Improving Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator

Adversarial examples can deceive a deep neural network (DNN) by signific...

11 Wenzhao Xiang, et al. ∙

research

∙ 07/29/2021

Tianshou: a Highly Modularized Deep Reinforcement Learning Library

We present Tianshou, a highly modularized python library for deep reinfo...

23 Jiayi Weng, et al. ∙

Hang Su

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