Abstract: We present an attention-based transformer learning approach for dynamic resource allocation in multi-carrier non-orthogonal multiple access (NOMA) downlink systems. We propose transformer ...

Abstract: Conventional Low-Rank Adaptation (LoRA) methods employ a fixed rank, imposing uniform adaptation across transformer layers and attention heads despite their heterogeneous learning dynamics.

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Though widely used, including in military systems, applications written in C and C++ are insecure. Adversaries can exploit their temporal memory safety errors to gain unauthorized access, exfiltrate ...

wolfIP is a TCP/IP stack with no dynamic memory allocations, designed to be used in resource-constrained embedded systems. Endpoint only mode is supported, which means that wolfip can be used to ...