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09/14/2023
Semantic Adversarial Attacks via Diffusion Models
Traditional adversarial attacks concentrate on manipulating clean exampl...
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09/01/2023
Reinforcement Learning with Human Feedback for Realistic Traffic Simulation
In light of the challenges and costs of real-world testing, autonomous v...
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08/28/2023
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing
Diffusion models have been leveraged to perform adversarial purification...
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06/28/2023
On the Exploitability of Instruction Tuning
Instruction tuning is an effective technique to align large language mod...
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06/27/2023
Differentially Private Video Activity Recognition
In recent years, differential privacy has seen significant advancements ...
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06/01/2023
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
Perception is crucial in the realm of autonomous driving systems, where ...
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05/25/2023
Voyager: An Open-Ended Embodied Agent with Large Language Models
We introduce Voyager, the first LLM-powered embodied lifelong learning a...
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05/24/2023
Adversarial Demonstration Attacks on Large Language Models
With the emergence of more powerful large language models (LLMs), such a...
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05/24/2023
From Shortcuts to Triggers: Backdoor Defense with Denoised PoE
Language models are often at risk of diverse backdoor attacks, especiall...
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05/24/2023
Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models
Instruction-tuned models are trained on crowdsourcing datasets with task...
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05/03/2023
Defending against Insertion-based Textual Backdoor Attacks via Attribution
Textual backdoor attack, as a novel attack model, has been shown to be e...
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04/27/2023
ChatGPT as an Attack Tool: Stealthy Textual Backdoor Attack via Blackbox Generative Model Trigger
Textual backdoor attacks pose a practical threat to existing systems, as...
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04/13/2023
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study
Large decoder-only language models (LMs) can be largely improved in term...
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03/30/2023
Mole Recruitment: Poisoning of Image Classifiers via Selective Batch Sampling
In this work, we present a data poisoning attack that confounds machine ...
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03/27/2023
Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency
Deep neural networks are proven to be vulnerable to backdoor attacks. De...
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03/04/2023
Prismer: A Vision-Language Model with An Ensemble of Experts
Recent vision-language models have shown impressive multi-modal generati...
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03/02/2023
Defending against Adversarial Audio via Diffusion Model
Deep learning models have been widely used in commercial acoustic system...
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02/23/2023
VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion
Humans can easily imagine the complete 3D geometry of occluded objects a...
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02/13/2023
PerAda: Parameter-Efficient and Generalizable Federated Learning Personalization with Guarantees
Personalized Federated Learning (pFL) has emerged as a promising solutio...
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02/09/2023
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning
Augmenting pretrained language models (LMs) with a vision encoder (e.g.,...
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11/01/2022
DensePure: Understanding Diffusion Models towards Adversarial Robustness
Diffusion models have been recently employed to improve certified robust...
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09/19/2022
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
Trajectory prediction is essential for autonomous vehicles (AVs) to plan...
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09/15/2022
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models
Pre-trained vision-language models (e.g., CLIP) have shown promising zer...
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08/23/2022
Retrieval-based Controllable Molecule Generation
Generating new molecules with specified chemical and biological properti...
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08/21/2022
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
3D Point cloud is becoming a critical data representation in many real-w...
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07/29/2022
Robust Trajectory Prediction against Adversarial Attacks
Trajectory prediction using deep neural networks (DNNs) is an essential ...
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07/25/2022
SecretGen: Privacy Recovery on Pre-Trained Models via Distribution Discrimination
Transfer learning through the use of pre-trained models has become a gro...
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05/16/2022
Diffusion Models for Adversarial Purification
Adversarial purification refers to a class of defense methods that remov...
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04/26/2022
Understanding The Robustness in Vision Transformers
Recent studies show that Vision Transformers(ViTs) exhibit strong robust...
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04/24/2022
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning
Reasoning about visual relationships is central to how humans interpret ...
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02/08/2022
Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models
Pre-trained language models (LMs) are shown to easily generate toxic lan...
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10/26/2021
AugMax: Adversarial Composition of Random Augmentations for Robust Training
Data augmentation is a simple yet effective way to improve the robustnes...
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09/25/2021
Auditing AI models for Verified Deployment under Semantic Specifications
Auditing trained deep learning (DL) models prior to deployment is vital ...
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07/05/2021
Long-Short Transformer: Efficient Transformers for Language and Vision
Transformers have achieved success in both language and vision domains. ...
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06/17/2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
In Autonomous Driving (AD) systems, perception is both security and safe...
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06/09/2021
Practical Machine Learning Safety: A Survey and Primer
The open-world deployment of Machine Learning (ML) algorithms in safety-...
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03/19/2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations
Deep Reinforcement Learning (DRL) is vulnerable to small adversarial per...
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07/21/2019
Characterizing Attacks on Deep Reinforcement Learning
Deep reinforcement learning (DRL) has achieved great success in various ...
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07/16/2019
Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving
In Autonomous Vehicles (AVs), one fundamental pillar is perception, whic...
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07/11/2019
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Deep neural networks (DNNs) are found to be vulnerable against adversari...
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06/19/2019
SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing
Deep neural networks (DNNs) have achieved great success in various appli...
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06/14/2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks
Training neural networks with verifiable robustness guarantees is challe...
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12/26/2018
Protecting Sensitive Attributes via Generative Adversarial Networks
Recent advances in computing have allowed for the possibility to collect...
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10/30/2018
Data Poisoning Attack against Unsupervised Node Embedding Methods
Unsupervised node embedding methods (e.g., DeepWalk, LINE, and node2vec)...
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10/11/2018
Realistic Adversarial Examples in 3D Meshes
Highly expressive models such as deep neural networks (DNNs) have been w...
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10/11/2018
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Deep Neural Networks (DNNs) have been widely applied in various recognit...
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01/08/2018
Spatially transformed adversarial examples
Recent studies show that widely used deep neural networks (DNNs) are vul...
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01/08/2018