Abstract: Transformers have become the backbone of large language decoder and encoder models, but their compute- and memory-intensive nature makes them inefficient on traditional von Neumann ...
Abstract: We propose a hardware-efficient optical matrix processor based on low-rank approximation, utilizing narrowband filters of microring resonators (MRRs) and broadband Mach-Zehnder ...
Abstract: This paper addresses the significant challenge of executing inference tasks involving General Matrix Multiplication (GEMM) in deep neural networks(DNN) on resource-constrained edge systems.
Recognition highlights Genpact's (G) AI-first, front-to-back banking operations capabilities across lending, payments, and servicing to deliver banking transformation NEW YORK, Jan. 22, 2026 ...
Abstract: The reconstruction of quantum states from experimental measurements, often achieved using quantum state tomography (QST), is crucial for the verification and benchmarking of quantum devices.
Abstract: This paper aims to address electromagnetic scattering problems in multiple bodies of revolution (MBoR) through a hybrid heterogeneous acceleration framework derived from equivalence ...
BURLINGTON, Mass., Dec. 9, 2025 /PRNewswire/ -- MatrixSpace, a leader in portable AI-enabled radar for counter-UAS (C-UAS), announces the availability of its revolutionary Portable 360 Radar™. This ...
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