Abstract: Noise in communication systems is interference factor that constrains radio modulation classification. To address the impact of interference on automatic modulation classification (AMC), we ...
AKDE provides an accurate, adaptive kernel density estimator based on the Gaussian Mixture Model for multidimensional data. This Python implementation includes automatic grid construction for ...
Why Policy-Conditioned Safety Matters? Conventional moderation models are trained on a single fixed policy. When that policy changes, the model must be retrained or replaced. gpt-oss-safeguard ...
According to OpenAI (@OpenAI), OpenAI has released GPT-OSS-Safeguard in research preview, introducing two open-weight reasoning models specifically designed for safety classification tasks. These AI ...
Objectives: To analyse stroke rate (SR) and stroke length (SL) combinations among elite swimmers to better understand stroke strategies across all race distances of freestyle events. Design: We ...
Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and ...
Abstract: To effectively address the challenges of undersampling techniques when handling imbalanced data, a new undersampling ensemble learning algorithm based on Kernel Density Estimation (KDEE) is ...
Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how ...
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