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Displaying 26 - 50 of 431

2024 NIST Generative AI (GenAI): Evaluation Plan for Text-to-Text (T2T) Discriminators

April 1, 2024
Author(s)
Yooyoung Lee, George Awad, Asad Butt, Lukas Diduch, Kay Peterson, Seungmin Seo, Ian Soboroff, Hariharan Iyer
Generator (G) teams will be tested on their system's ability to generate content that is indistinguishable from human-generated content. For the pilot study, the evaluation will help determine strengths and weaknesses in their approaches including insights

AI Use Taxonomy: A Human-Centered Approach

March 26, 2024
Author(s)
Mary Frances Theofanos, Yee-Yin Choong, Theodore Jensen
As artificial intelligence (AI) systems continue to be developed, humans will increasingly participate in human-AI interactions. Humans interact with AI systems to achieve particular goals. To ensure that AI systems contribute positively to human-AI

Improving the TENOR of Labeling: Re-evaluating Topic Models for Content Analysis

March 23, 2024
Author(s)
Zongxia Li, Andrew Mao, Jordan Boyd-Graber, Daniel Stephens, Emily Walpole, Alden A. Dima, Juan Fung
Topic models are a popular tool for understanding text collections, but their evaluation has been a point of contention. Automated evaluation metrics such as coherence are often used, however, their validity has been questioned for neural topic models

Photonic Online Learning

January 9, 2024
Author(s)
Sonia Buckley, Adam McCaughan, Bakhrom Oripov
Training in machine learning necessarily involves more operations than inference only, with higher precision, more memory, and added computational complexity. In hardware, many implementations side-step this issue by designing "inference-only" hardware

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

January 4, 2024
Author(s)
Apostol Vassilev, Alina Oprea, Alie Fordyce, Hyrum Andersen
This NIST AI report develops a taxonomy of concepts and defines terminology in the field of adversarial machine learning (AML). The taxonomy is built on survey of the AML literature and is arranged in a conceptual hierarchy that includes key types of ML

Facilitating Stakeholder Communication around AI-Enabled Systems and Business Processes

November 21, 2023
Author(s)
Edward Griffor, Matthew Bundas, Chasity Nadeau, Jeannine Shantz, Thanh Nguyen, Marcello Balduccini, Tran Son
Artificial Intelligence (AI) is often critical to the success of modern business processes. Leveraging it, however, is non-trivial. A major hurdle is communication: discussing system requirements among stakeholders with different backgrounds and goals

2022 OpenFAD Evaluation Plan (Open Fine-grained Activity Detection)

October 2, 2023
Author(s)
Yooyoung Lee, Jonathan Fiscus, Lukas Diduch, Jeffery Byrne
This document describes an evaluation of the 2022 Open Fine-grained Activity Detection (OpenFAD) challenge. The evaluation plan covers resources, task definitions, task conditions, file formats for system inputs and outputs, evaluation metrics, scoring

Labeling Software Security Vulnerabilities

October 1, 2023
Author(s)
Irena Bojanova, John Guerrerio
Labeling software security vulnerabilities would benefit greatly modern artificial intelligence cybersecurity research. The National Vulnerability Database (NVD) partially achieves this via assignment of Common Weakness Enumeration (CWE) entries to Common

Neural networks three ways: unlocking novel computing schemes using magnetic tunnel junction stochasticity

September 28, 2023
Author(s)
Matthew Daniels, William Borders, Nitin Prasad, Advait Madhavan, Sidra Gibeault, Temitayo Adeyeye, Liam Pocher, Lei Wan, Michael Tran, Jordan Katine, Daniel Lathrop, Brian Hoskins, Tiffany Santos, Patrick Braganca, Mark Stiles, Jabez J. McClelland
Due to their interesting physical properties, myriad operational regimes, small size, and industrial fabrication maturity, magnetic tunnel junctions are uniquely suited for unlocking novel computing schemes for in-hardware neuromorphic computing. In this

Tuning Arrays with Rays: Physics-Informed Tuning of Quantum Dot Charge States

September 28, 2023
Author(s)
Joshua Ziegler, Florian Luthi, Mick Ramsey, Felix Borjans, Guoji Zheng, Justyna Zwolak
Quantum computers based on gate-defined quantum dots (QDs) are expected to scale. However, as the number of qubits increases, the burden of manually calibrating these systems becomes unreasonable and autonomous tuning must be used. There has been a range

Comparison of Ice-on-Coil Thermal Energy Storage Models

September 13, 2023
Author(s)
Kalyan Ram Kanagala, Amanda Pertzborn
Data collected from the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST) are used to develop a physics-based and four machine learning models of ice-on-coil thermal energy storage (TES): linear

RECENT DEVELOPMENTS IN ONTOLOGY STANDARDS AND THEIR APPLICABILITY TO BIOMANUFACTURING

July 14, 2023
Author(s)
Milos Drobnjakovic, Boonserm Kulvatunyou, Simon P. Frechette, Vijay Srinivasan
ISO and IEC have jointly initiated, and recently issued, a series of standards (the ISO/IEC 21838 series) for top-level ontologies. These standards have been used by industrial consortia to develop and disseminate standards for mid-level ontologies to ease

O-RAN with Machine Learning in ns-3

June 28, 2023
Author(s)
Wesley Garey, Richard A. Rouil, Evan Black, Tanguy Ropitault, Weichao Gao
The Open Radio Access Network (O-RAN) Alliance is the industry led standardization effort, with the sole purpose of evolving the Radio Access Network (RAN) to be more open, intelligent, interoperable, and autonomous to support the ever growing need of

2022 Cybersecurity & Privacy Annual Report

May 30, 2023
Author(s)
Patrick D. O'Reilly, Kristina Rigopoulos, Larry Feldman, Greg Witte
During Fiscal Year 2022 (FY 2022) – from October 1, 2021, through September 30, 2022 –the NIST Information Technology Laboratory (ITL) Cybersecurity and Privacy Program successfully responded to numerous challenges and opportunities in security and privacy

Automated extraction of capacitive coupling for quantum dot systems

May 24, 2023
Author(s)
Joshua Ziegler, Florian Luthi, Mick Ramsey, Felix Borjans, Guoji Zheng, Justyna Zwolak
Gate-defined quantum dots (QDs) have appealing attributes as a quantum computing platform. However, near-term devices possess a range of possible imperfections that need to be accounted for during the tuning and operation of QD devices. One such problem is
Displaying 26 - 50 of 431