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Found 8 papers, 4 papers with code
Have You Merged My Model? On The Robustness of Large Language Model IP Protection Methods Against Model Merging
Model merging is a promising lightweight model empowerment technique that does not rely on expensive computing devices (e. g., GPUs) or require the collection of specific training data.
Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler
Digital twin, which enables emulation, evaluation, and optimization of physical entities through synchronized digital replicas, has gained increasingly attention as a promising technology for intricate wireless networks.
FigStep: Jailbreaking Large Vision-language Models via Typographic Visual Prompts
Ensuring the safety of artificial intelligence-generated content (AIGC) is a longstanding topic in the artificial intelligence (AI) community, and the safety concerns associated with Large Language Models (LLMs) have been widely investigated.
Multi-task Learning-based CSI Feedback Design in Multiple Scenarios
One efficient CSI feedback method is the Auto-Encoder (AE) structure based on deep learning, yet facing problems in actual deployments, such as selecting the deployment mode when deploying in a cell with multiple complex scenarios.
Energy-based Out-of-distribution Detection
We propose a unified framework for OOD detection that uses an energy score.
GraphDefense: Towards Robust Graph Convolutional Networks
Inspired by the previous works on adversarial defense for deep neural networks, and especially adversarial training algorithm, we propose a method called GraphDefense to defend against the adversarial perturbations.
Attack Graph Convolutional Networks by Adding Fake Nodes
In this paper, we propose a new type of "fake node attacks" to attack GCNs by adding malicious fake nodes.
Phoneme Set Design Using English Speech Database by Japanese for Dialogue-Based English CALL Systems
This paper describes a method of generating a reduced phoneme set for dialogue-based computer assisted language learning (CALL)systems.
