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Found 19 papers, 4 papers with code
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
Currently, existing surveys on LLM safety primarily focus on specific stages of the LLM lifecycle, e. g., deployment phase or fine-tuning phase, lacking a comprehensive understanding of the entire "lifechain" of LLMs.
PATFinger: Prompt-Adapted Transferable Fingerprinting against Unauthorized Multimodal Dataset Usage
The multimodal datasets can be leveraged to pre-train large-scale vision-language models by providing cross-modal semantics.
\textsc{Perseus}: Tracing the Masterminds Behind Cryptocurrency Pump-and-Dump Schemes
Previous research detects pump-and-dump activities in the market, predicts the target cryptocurrency, and examines investors and \ac{osn} entities.
Exploiting Vulnerabilities in Speech Translation Systems through Targeted Adversarial Attacks
As speech translation (ST) systems become increasingly prevalent, understanding their vulnerabilities is crucial for ensuring robust and reliable communication.
Secure Resource Allocation via Constrained Deep Reinforcement Learning
The proliferation of Internet of Things (IoT) devices and the advent of 6G technologies have introduced computationally intensive tasks that often surpass the processing capabilities of user devices.
Rethinking Membership Inference Attacks Against Transfer Learning
The interaction between teacher and student models in transfer learning has not been thoroughly explored in MIAs, potentially resulting in an under-examined aspect of privacy vulnerabilities within transfer learning.
LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks
However, the intermittent connectivity between LEO satellites and ground station (GS) significantly hinders the timely transmission of raw data to GS for centralized learning, while the scaled-up DL models hamper distributed learning on resource-constrained LEO satellites.
Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections
The shared topology of human skeletons motivated the recent investigation of graph convolutional network (GCN) solutions for action recognition.
HeteroSample: Meta-path Guided Sampling for Heterogeneous Graph Representation Learning
Efficient analysis of these graphs is critical for deriving insights in IoT scenarios such as smart cities, industrial IoT, and intelligent transportation systems.
An Efficient Privacy-aware Split Learning Framework for Satellite Communications
Our framework not only significantly improves the operational efficiency of satellite communications but also establishes a new benchmark in privacy-aware distributed learning, potentially revolutionizing data handling in space-based networks.
Privacy-preserving Universal Adversarial Defense for Black-box Models
Comparative evaluations between the certified defenses of the surrogate and target models demonstrate the effectiveness of our approach.
An Improved Graph Pooling Network for Skeleton-Based Action Recognition
Pooling is a crucial operation in computer vision, yet the unique structure of skeletons hinders the application of existing pooling strategies to skeleton graph modelling.
CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning
The detection models exhibited vulnerabilities, with FAR rising to 36. 69%, 31. 23%, and 51. 28% under volume control, fading, and noise injection, respectively.
On the Effectiveness of Distillation in Mitigating Backdoors in Pre-trained Encoder
Distillation aims to distill knowledge from a given model (a. k. a the teacher net) and transfer it to another (a. k. a the student net).
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition
Contrastive learning has achieved great success in skeleton-based action recognition.
The Multi-Modal Video Reasoning and Analyzing Competition
In this paper, we introduce the Multi-Modal Video Reasoning and Analyzing Competition (MMVRAC) workshop in conjunction with ICCV 2021.
CryptMPI: A Fast Encrypted MPI Library
The cloud infrastructure must provide security for High-Performance Computing (HPC) applications of sensitive data to execute in such an environment.
Distributed, Parallel, and Cluster Computing Cryptography and Security
Performance Evaluation and Modeling of Cryptographic Libraries for MPI Communications
In order for High-Performance Computing (HPC) applications with data security requirements to execute in the public cloud, the cloud infrastructure must ensure the privacy and integrity of data.
Distributed, Parallel, and Cluster Computing Cryptography and Security
Spatial Residual Layer and Dense Connection Block Enhanced Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition
In order to capture the rich spatiotemporal information and utilize features more effectively, we introduce a spatial residual layer and a dense connection block enhanced spatial temporal graph convolutional network.
Ranked #58 on
Skeleton Based Action Recognition
on NTU RGB+D
