Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...
Abstract: Multi-scalar multiplication (MSM) is the primary computational bottleneck in zero-knowledge proof protocols. To address this, we introduce FAMA, an FPGA-oriented MSM accelerator developed ...
Abstract: This paper aims to provide a comparative analysis of low-power design methods for the implementation of the Arithmetic Logical Unit using Fin- Field Effective Transistor. The study evaluates ...
Abstract: This paper focuses on the multi-objective resource allocation problem in multi-agent systems, where the objective is to find an optimal allocation policy. To solve this problem, we propose ...
Abstract: Many practical antennas contain continuous, binary, and categorical geometrical variables. Antenna designs involving such mixed-type variables fall under the category of mixed-variable ...
Abstract: At terahertz (THz) band, the beam tunnel size becomes very small and requires an in-depth analysis of electron beam focusing behavior for a THz traveling wave tube (TWT). A nonlaminar beam ...
Abstract: Nonrigid point set registration (NRPSR) is a fundamental research area in the domains of robotics and industrial measurement, aiming to estimate the correspondence and spatial transformation ...
Abstract: Glass manufacturing processes often yield complex defects such as bubbles, stones, and scratches. While machine vision systems powered by deep learning offer effective defect detection, real ...
Abstract: SNN deployment faces a dilemma: rate codes are power-hungry while temporal codes lack noise resilience. This paper proposes an SNN algorithm-hardware co-design, which uses sparse coding and ...
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If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...
As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
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