Zobrazeno 1 - 10
of 9 689
pro vyhledávání: '"Robustness evaluation"'
As deep learning models are increasingly deployed in safety-critical applications, evaluating their vulnerabilities to adversarial perturbations is essential for ensuring their reliability and trustworthiness. Over the past decade, a large number of
Externí odkaz:
http://arxiv.org/abs/2411.15210
Offline reinforcement learning, which learns solely from datasets without environmental interaction, has gained attention. This approach, similar to traditional online deep reinforcement learning, is particularly promising for robot control applicati
Externí odkaz:
http://arxiv.org/abs/2412.18781
Autor:
Wang, Yongyu
Graph Neural Networks (GNNs) are currently one of the most powerful types of neural network architectures. Their advantage lies in the ability to leverage both the graph topology, which represents the relationships between samples, and the features o
Externí odkaz:
http://arxiv.org/abs/2412.10850
The Physical Internet (PI) paradigm, which has gained attention in research and academia in recent years, leverages advanced logistics and interconnected networks to revolutionize the way goods are transported and delivered, thereby enhancing efficie
Externí odkaz:
http://arxiv.org/abs/2412.14658
Autor:
Kahl, Kim-Celine, Erkan, Selen, Traub, Jeremias, Lüth, Carsten T., Maier-Hein, Klaus, Maier-Hein, Lena, Jaeger, Paul F.
Vision-Language Models (VLMs) have great potential in medical tasks, like Visual Question Answering (VQA), where they could act as interactive assistants for both patients and clinicians. Yet their robustness to distribution shifts on unseen data rem
Externí odkaz:
http://arxiv.org/abs/2411.19688
Vision Language Models (VLMs) extend remarkable capabilities of text-only large language models and vision-only models, and are able to learn from and process multi-modal vision-text input. While modern VLMs perform well on a number of standard image
Externí odkaz:
http://arxiv.org/abs/2409.18023
In this paper, we propose privacy-preserving methods with a secret key for convolutional neural network (CNN)-based models in speech processing tasks. In environments where untrusted third parties, like cloud servers, provide CNN-based systems, ensur
Externí odkaz:
http://arxiv.org/abs/2408.03897
Autor:
Khattak, Muhammad Uzair, Naeem, Muhammad Ferjad, Hassan, Jameel, Naseer, Muzammal, Tombari, Federico, Khan, Fahad Shahbaz, Khan, Salman
Recent advancements in Large Language Models (LLMs) have led to the development of Video Large Multi-modal Models (Video-LMMs) that can handle a wide range of video understanding tasks. These models have the potential to be deployed in real-world app
Externí odkaz:
http://arxiv.org/abs/2405.03690
Publikováno v:
In Information and Software Technology March 2025 179
Deep learning has enabled great strides in abdominal multi-organ segmentation, even surpassing junior oncologists on common cases or organs. However, robustness on corner cases and complex organs remains a challenging open problem for clinical adopti
Externí odkaz:
http://arxiv.org/abs/2406.13674