This recommended practice provides a comprehensive framework for understanding, defining, and evaluating AI risks, AI safety, AI trustworthiness, and AI…
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IEEE P3419
Standard for Large Language Model Evaluation
This standard establishes a comprehensive set of criteria for the evaluation of Large Language Models (LLMs) and extends to multimodal…
For the software engineering life cycle empowered by Generative Pre-trained Transformer (GPT) this recommended practice specifies: • a description and…
This standard addresses Artificial Intelligence (AI) risks such as malicious use, AI race, organizational risks, and rogue AI’s. The standard…
This recommended practice provides a data processing framework for training large language models, refining the relevant terms and definitions. The…
This standard specifies the basic functions, performance requirements, software ecosystem, and application scenarios of the deep learning chip for the…
The standard specifies a type of compilation interface and its intermediate representation used for deep learning model computation tasks. This…
This standard applies to the design, development, application, and evaluation of large-scale deep learning models for artificial intelligence. The standard…
This recommended practice specifies tools and indexes for evaluating content generated by artificial intelligence technology. © Copyright 2024 IEEE –…
This recommended practice specifies the general requirements of three dimensional (3D) object reconstruction based on deep learning, including terminology, requirements…
This standard defines a unified text approach to describing neural network architectures. This standard specifies data requirements, coding formats of…
This standard outlines the toolchain for deploying artificial intelligence (AI) models on edge devices and specifies the functional requirements for…
