Zobrazeno 1 - 10
of 3 740
pro vyhledávání: '"inference attack"'
Recent advances in Large Language Models (LLMs) have enabled them to overcome their context window limitations, and demonstrate exceptional retrieval and reasoning capacities on longer context. Quesion-answering systems augmented with Long-Context La
Externí odkaz:
http://arxiv.org/abs/2411.11424
Source Inference Attack (SIA) in Federated Learning (FL) aims to identify which client used a target data point for local model training. It allows the central server to audit clients' data usage. In cross-silo FL, a client (silo) collects data from
Externí odkaz:
http://arxiv.org/abs/2409.19417
Masked Image Modeling (MIM) has achieved significant success in the realm of self-supervised learning (SSL) for visual recognition. The image encoder pre-trained through MIM, involving the masking and subsequent reconstruction of input images, attain
Externí odkaz:
http://arxiv.org/abs/2408.06825
Autor:
Li, Hao, Li, Zheng, Wu, Siyuan, Hu, Chengrui, Ye, Yutong, Zhang, Min, Feng, Dengguo, Zhang, Yang
Most existing membership inference attacks (MIAs) utilize metrics (e.g., loss) calculated on the model's final state, while recent advanced attacks leverage metrics computed at various stages, including both intermediate and final stages, throughout
Externí odkaz:
http://arxiv.org/abs/2407.15098
With the rapid advancements of large-scale text-to-image diffusion models, various practical applications have emerged, bringing significant convenience to society. However, model developers may misuse the unauthorized data to train diffusion models.
Externí odkaz:
http://arxiv.org/abs/2407.13252
The advent and growing popularity of Virtual Reality (VR) and Mixed Reality (MR) solutions have revolutionized the way we interact with digital platforms. The cutting-edge gaze-controlled typing methods, now prevalent in high-end models of these devi
Externí odkaz:
http://arxiv.org/abs/2409.08122
Autor:
Ahamed, Sayyed Farid, Banerjee, Soumya, Roy, Sandip, Quinn, Devin, Vucovich, Marc, Choi, Kevin, Rahman, Abdul, Hu, Alison, Bowen, Edward, Shetty, Sachin
Over the last few years, federated learning (FL) has emerged as a prominent method in machine learning, emphasizing privacy preservation by allowing multiple clients to collaboratively build a model while keeping their training data private. Despite
Externí odkaz:
http://arxiv.org/abs/2407.19119
As a solution concept in cooperative game theory, Shapley value is highly recognized in model interpretability studies and widely adopted by the leading Machine Learning as a Service (MLaaS) providers, such as Google, Microsoft, and IBM. However, as
Externí odkaz:
http://arxiv.org/abs/2407.11359
Large Language Models (LLMs) have seen widespread adoption due to their remarkable natural language capabilities. However, when deploying them in real-world settings, it is important to align LLMs to generate texts according to acceptable human stand
Externí odkaz:
http://arxiv.org/abs/2407.06443
Given the rising popularity of AI-generated art and the associated copyright concerns, identifying whether an artwork was used to train a diffusion model is an important research topic. The work approaches this problem from the membership inference a
Externí odkaz:
http://arxiv.org/abs/2405.20771