1.1 This practice considers impairments of communications within an automatic, automated, or autonomous unmanned ground vehicle (AĀUGV) system during task…
United States
This standard provides definitions, terms, frameworks, and general requirements for systems that apply pre-trained large language models (LLM) in the…
This document is a guide and record of the development for the NIST (National Institute of Standards and Technology) glossary…
This recommended practice specifies the general requirements of three dimensional (3D) object reconstruction based on deep learning, including terminology, requirements…
This standard provides: 1. Agent Components: The building blocks and architectural elements that constitute an educational Large Language Model (LLM)…
This standard establishes a comprehensive set of criteria for the evaluation of Large Language Models (LLMs) and extends to multimodal…
This standard establishes a comprehensive framework for mitigating security risks, privacy leaking in the development, deployment, and use of generative…
This standard addresses Artificial Intelligence (AI) risks such as malicious use, AI race, organizational risks, and rogue AI’s. The standard…
The purpose of this standard is to define elements to improve transparency in the identification of the agency behind media…
This standard addresses the evaluation of safety, explainability, and stability of algorithms implementing autonomous driving levels, as defined by SAE…
This document specifies a method for evaluating the fairness of machine learning. Multiple causes contribute to the unfairness of machine…
This standard defines a comprehensive framework for federated machine learning of semantic information agents. It targets two primary layers: ⢅