Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...
Abstract: The rapid expansion of large language models (LLMs) has led to increasingly frequent interactions between LLM agents and human users, motivating new questions about their capacity to form ...
Modeling Person Guessing as a Random Effect: A Bayesian Approach of the Two-Parameter Logistic Model
The final, formatted version of the article will be published soon. Guessing behavior has been an enduring problem that undermines the validity and interpretability of scores from MC items. The ...
These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
Try it out via this demo. bitnet.cpp is the official inference framework for 1-bit LLMs (e.g., BitNet b1.58). It offers a suite of optimized kernels, that support fast and lossless inference of ...
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results