U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Search Publications

NIST Authors in Bold

Displaying 1 - 25 of 438

2024 NIST GenAI (Pilot Study): Text-to-Text Evaluation Overview and Results

June 25, 2025
Author(s)
Hariharan Iyer, Seungmin Seo, Lukas Diduch, Kay Peterson, George Awad, Yooyoung Lee
The 2024 NIST Generative AI (GenAI) Pilot Study focuses on evaluating text-to-text (T2T) generation and discrimination tasks to assess the capabilities and limitations of generative AI models and AI detectors. The study aims to measure the effectiveness of

Hallucination Detection in Large Language Models Using Diversion Decoding

June 24, 2025
Author(s)
Basel Abdeen, S M Tahmid Siddiqui, Meah Tahmeed Ahmed, Anoop Singhal, Latifur Khan, Punya Modi, Ehab Al-Shaer
Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advanced text generation capabilities, LLMs exhibit hallucination tendencies, where they generate factually

NIST GenAI (Pilot): an Overview of Text-to-Text Evaluation Results

May 5, 2025
Author(s)
Yooyoung Lee, Hariharan Iyer
The 2024 NIST Generative AI (GenAI) Pilot Study focuses on evaluating text-to-text (T2T) generation and discrimination tasks to assess the capabilities and limitations of generative AI models. The study aims to measure the effectiveness of AI-generated

A Plan for Global Engagement on AI Standards

April 29, 2025
Author(s)
Jesse Dunietz, Mark Latonero, Kathleen Roberts
This plan has been developed by the Department of Commerce in coordination with the Department of State and agencies across the U.S. Government. It reflects more than 65 comments received in response to a December 2023 Request for Information

Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

March 24, 2025
Author(s)
Apostol Vassilev, Alina Oprea, Alie Fordyce, Hyrum Anderson, Xander Davies, Maia Hamin
This NIST Trustworthy and Responsible AI report provides a taxonomy of concepts and defines terminology in the field of adversarial machine learning (AML). The taxonomy is arranged in a conceptual hierarchy that includes key types of ML methods, life cycle

Detection limits of AI-based SEM dimensional metrology

March 14, 2025
Author(s)
Peter Bajcsy, Brycie Wiseman, Michael Paul Majurski, Andras Vladar
The speed of in-line scanning electron microscope (SEM) measurements of linewidth, contact hole, and overlay is critically important for identifying the measurement area and generating indispensable process control information. Sample charging and damage

Semantics for Enhancing Communications- and Edge-Intelligence-enabled Smart Sensors: A Practical Use Case in Federated Automotive Diagnostics

March 10, 2025
Author(s)
Eugene Song, Thomas Roth, David A. Wollman, Eoin Jordan, Martin Serrano, Amelie Gyrard
Modern edge artificial intelligence (AI) chipsets and edge-intelligence-enabled smart sensors frameworks support real-time data processing and event detection at the signal source. Beyond just measuring local conditions and transmitting corresponding

NIST Open Media Forensics Challenge (OpenMFC Briefing for IIRD)

January 27, 2025
Author(s)
Haiying Guan
The rapid advancement of artificial intelligence (AI) has led to the emergence of several technologies, including Generative Adversarial Networks (GANs), deepfakes, generative AI, CGI, and anti-forensics techniques. These technologies pose a significant

Reflection of its Creators: Qualitative Analysis of General Public and Expert Perceptions of Artificial Intelligence

October 16, 2024
Author(s)
Theodore Jensen, Mary Frances Theofanos, Kristen K. Greene, Olivia Williams, Kurtis Goad, Janet Bih Fofang
The increasing prevalence of artificial intelligence (AI) will likely lead to new interactions and impacts for the general public. An understanding of people's perceptions of AI can be leveraged to design and deploy AI systems toward human needs and values

An Overarching Quality Evaluation Framework for Additive Manufacturing Digital Twin

September 2, 2024
Author(s)
Yan Lu, Zhuo Yang, Shengyen Li, Yaoyao Fiona Zhao, Jiarui Xie, Mutahar Safdar, Hyunwoong Ko
The key differentiation of digital twins from existing models-based engineering approaches lies in the continuous synchronization between physical and virtual twins through data exchange. The success of digital twins, whether operated automatically or with

A Plan for Global Engagement on AI Standards

July 26, 2024
Author(s)
Jesse Dunietz, Elham Tabassi, Mark Latonero, Kamie Roberts
Recognizing the importance of technical standards in shaping development and use of Artificial Intelligence (AI), the President's October 2023 Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (EO 14110)

Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile

July 26, 2024
Author(s)
Chloe Autio, Reva Schwartz, Jesse Dunietz, Shomik Jain, Martin Stanley, Elham Tabassi, Patrick Hall, Kamie Roberts
This document is a cross-sectoral profile of and companion resource for the AI Risk Management Framework (AI RMF 1.0) for Generative AI, pursuant to President Biden's Executive Order (EO) 14110 on Safe, Secure, and Trustworthy Artificial Intelligence. The

Forecasting Operation of a Chiller Plant Facility Using Data Driven Models

July 23, 2024
Author(s)
Behzad Salimian Rizi, Afshin Faramarzi, Amanda Pertzborn, Mohammad Heidarinejad
In recent years, data-driven models have enabled accurate prediction of chiller power consumption and chiller coefficient of performance (COP). This study evaluates the usage of time series Extreme Gradient Boosting (XGBoost) models to predict chiller
Displaying 1 - 25 of 438
Was this page helpful?