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09/18/2023
Evaluation of GPT-3 for Anti-Cancer Drug Sensitivity Prediction
In this study, we investigated the potential of GPT-3 for the anti-cance...
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07/31/2023
Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples
Deep Neural Networks (DNNs) for 3D point cloud recognition are vulnerabl...
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07/12/2023
Instruction Mining: High-Quality Instruction Data Selection for Large Language Models
Large language models typically undergo two training stages, pretraining...
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06/20/2023
TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Models
Large Language Models (LLMs) such as ChatGPT, have gained significant at...
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06/13/2023
A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning
Offline reinforcement learning (RL) provides a promising solution to lea...
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06/12/2023
Scalable Fair Influence Maximization
Given a graph G, a community structure 𝒞, and a budget k, the fair influ...
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06/08/2023
FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs
This paper introduces FedMLSecurity, a benchmark that simulates adversar...
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06/08/2023
Instructed Diffuser with Temporal Condition Guidance for Offline Reinforcement Learning
Recent works have shown the potential of diffusion models in computer vi...
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06/02/2023
Decentralized Federated Learning: A Survey and Perspective
Federated learning (FL) has been gaining attention for its ability to sh...
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05/25/2023
DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models
Recently, Generative Diffusion Models (GDMs) have showcased their remark...
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05/22/2023
Watermarking Text Data on Large Language Models for Dataset Copyright Protection
Large Language Models (LLMs), such as BERT and GPT-based models like Cha...
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03/08/2023
Memory-adaptive Depth-wise Heterogenous Federated Learning
Federated learning is a promising paradigm that allows multiple clients ...
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03/07/2023
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining signif...
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03/05/2023
Unlearnable Graph: Protecting Graphs from Unauthorized Exploitation
While the use of graph-structured data in various fields is becoming inc...
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03/05/2023
Securing Biomedical Images from Unauthorized Training with Anti-Learning Perturbation
The volume of open-source biomedical data has been essential to the deve...
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02/18/2023
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
The Pretrained Foundation Models (PFMs) are regarded as the foundation f...
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02/18/2023
Backdoor Attacks to Pre-trained Unified Foundation Models
The rise of pre-trained unified foundation models breaks down the barrie...
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02/07/2023
SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency
Deep neural networks (DNNs) are vulnerable to backdoor attacks, where ad...
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01/02/2023
Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding
Temporal sentence grounding (TSG) aims to identify the temporal boundary...
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12/06/2022
Tackling Data Heterogeneity in Federated Learning with Class Prototypes
Data heterogeneity across clients in federated learning (FL) settings is...
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11/23/2022
SEAT: Stable and Explainable Attention
Currently, attention mechanism becomes a standard fixture in most state-...
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11/22/2022
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples
Point cloud completion, as the upstream procedure of 3D recognition and ...
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10/18/2022
Transferable Unlearnable Examples
With more people publishing their personal data online, unauthorized dat...
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10/14/2022
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning
Multi-agent reinforcement learning has drawn increasing attention in pra...
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09/02/2022
Scalable Adversarial Attack Algorithms on Influence Maximization
In this paper, we study the adversarial attacks on influence maximizatio...
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06/18/2022
Fully Privacy-Preserving Federated Representation Learning via Secure Embedding Aggregation
We consider a federated representation learning framework, where with th...
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06/10/2022
Membership Inference via Backdooring
Recently issued data privacy regulations like GDPR (General Data Protect...
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05/25/2022
End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models
We propose the end-to-end multimodal fact-checking and explanation gener...
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05/08/2022
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks
Graph neural networks (GNNs) have been widely used in modeling graph str...
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03/17/2022
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation
Federated Learning (FL) on knowledge graphs (KGs) has yet to be as well ...
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11/29/2021
FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization
The underlying assumption of recent federated learning (FL) paradigms is...
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11/21/2021
Structure-Preserving Graph Kernel for Brain Network Classification
This paper presents a novel graph-based kernel learning approach for con...
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10/14/2021
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding
Event extraction is typically modeled as a multi-class classification pr...
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10/07/2021
DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems
Depth estimation-based obstacle avoidance has been widely adopted by aut...
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09/13/2021
Source Inference Attacks in Federated Learning
Federated learning (FL) has emerged as a promising privacy-aware paradig...
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09/03/2021
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
Since training a large-scale backdoored model from scratch requires a la...
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08/26/2021
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN
In the information explosion era, recommender systems (RSs) are widely s...
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08/17/2021
HAWK: Rapid Android Malware Detection through Heterogeneous Graph Attention Networks
Android is undergoing unprecedented malicious threats daily, but the exi...
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07/31/2021
Multiplex Graph Networks for Multimodal Brain Network Analysis
In this paper, we propose MGNet, a simple and effective multiplex graph ...
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07/07/2021
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis
Multimodal brain networks characterize complex connectivities among diff...
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06/30/2021
Global Knowledge Distillation in Federated Learning
Knowledge distillation has caught a lot of attention in Federated Learni...
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06/25/2021
Subgraph Federated Learning with Missing Neighbor Generation
Graphs have been widely used in data mining and machine learning due to ...
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05/23/2021
Killing Two Birds with One Stone: Stealing Model and Inferring Attribute from BERT-based APIs
The advances in pre-trained models (e.g., BERT, XLNET and etc) have larg...
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05/07/2021
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks
Graph representation learning has achieved great success in many areas, ...
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05/04/2021
Federated Multi-View Learning for Private Medical Data Integration and Analysis
Along with the rapid expansion of information technology and digitalizat...
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04/25/2021
User Preference-aware Fake News Detection
Disinformation and fake news have posed detrimental effects on individua...
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04/16/2021
Membership Inference Attacks on Knowledge Graphs
Knowledge graphs have become increasingly popular supplemental informati...
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03/18/2021
Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!
Natural language processing (NLP) tasks, ranging from text classificatio...
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02/06/2021
FedMood:Federated Learning on Mobile Health Data for Mood Detection
Depression is one of the most common mental illness problems, and the sy...
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12/07/2020