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The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

In classical vernacular Chinese fiction, inferring affective stance in the presence of rhetorical devices often depends on implicit semantics and contextual cues, which poses substantial challenges for joint pragmatic mo...

Short-term wind speed forecasting remains challenging due to the inherent nonstationarity and multiscale variability of atmospheric processes. This study proposes a hybrid multiscale forecasting framework combining four-...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

Artificial intelligence (AI) models developed for Global Navigation Satellite System Reflectometry (GNSS-R) observations have demonstrated competitive performance in estimating geophysical parameters, especially ocean su...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

The Fast Steering Mirror (FSM) is a critical beam steering component in precision optical systems. However, its design often relies on repetitive finite element analysis (FEM) and experimentation due to the lack of unive...

The perception systems for Traffic Sign Recognition (TSR) and Lane Line Recognition (LLR) are foundational pillars for the safe and effective operation of Advanced Driver-Assistance Systems (ADAS) and fully autonomous ve...