Photopolymer Additive Manufacturing 2025 Workshop Report: Building a Unified Vision from Research to Regulation
The third biannual Photopolymer Additive Manufacturing Alliance Workshop was held on September 15-16, 2025, at the University of Colorado Boulder to continue its mission of advancing photopolymer additive manufacturing (PAM). Building on the 2023 PAMA
Technical Specification for the Security Content Automation Protocol (SCAP) SCAP Version 1.4
The Security Content Automation Protocol (SCAP) is a suite of specifications that standardize the format and nomenclature by which software flaw and security configuration information is communicated, both to machines and humans. This publication, along
SCAP 1.4 Component Specification Version Updates: An Annex to NIST SP 800-126r4
The Security Content Automation Protocol (SCAP) is a multi-purpose framework of component specifications that support automated configuration, vulnerability, patch checking, security measurement, and technical control compliance activities. The SCAP
STAMP: A Species- and Topic-Aware Multimodal Predictor for Cross-Species Antimicrobial Peptide Activity
Antimicrobial resistance poses a major global health challenge, necessitating efficient strategies for discovering potent antimicrobial peptides (AMPs). While recent generative models can produce large numbers of candidate sequences, experimentally
A generative pre-trained transformer with Kerr-soliton attention
Artificial intelligence systems, particularly through generative pre-trained transformers (GPTs), have enabled capability-rich language models, but their operation incurs substantial costs in digital computation, memory, and data movement. Attention is a
Fiscal Year 2025 Annual Report for NIST Cybersecurity and Privacy Program
Throughout Fiscal Year 2025 (FY 2025) — from October 1, 2024, through September 30, 2025 — the NIST Information Technology Laboratory (ITL) Cybersecurity and Privacy Program successfully responded to numerous challenges and opportunities in security and
Summary Analysis of Responses to the Request for Information Regarding Security Considerations for AI Agents
This report provides an overview of the responses to a Request for Information (RFI) issued by the U.S. Center for AI Standards and Innovation (CAISI) on the state of artificial intelligence (AI) agent security. Commenters were asked for input on the
Explainable Validation and Feature Reduction in Machine Learning
Although there are many available approaches for designing machine learning models and experiments, not all of these approaches are explainable or interpretable. Combination frequency differencing (CFD) provides information on the relationship between
Advancing Human-Centered Cybersecurity: Challenges and Pathways Forward
We present the key themes from the workshop "ConnectCon: Minding the Gaps in Human-Centered Cybersecurity," which can inform efforts of researchers and practitioners toward a collective goal of improving cybersecurity outcomes for all.
Robust AI Security and Alignment: A Sisyphean Endeavor?
This article establishes information-theoretic limitations for robustness of artificial intelligence (AI) security and alignment. Knowing these limitations and preparing for their challenges is essential for responsible adoption of AI. Broader implications
Nondestructive characterization of laser-cooled atoms using machine learning
We develop machine learning techniques for estimating physical properties of laser-cooled potassium-39 atoms in a magneto-optical trap using only the scattered light---i.e., fluorescence---that is intrinsic to the cooling process. In-situ snap-shot images
Enhanced Security Requirements for Protecting Controlled Unclassified Information
The protection of Controlled Unclassified Information (CUI) resident in nonfederal systems and organizations is of paramount importance to federal agencies and can directly impact the ability of the Federal Government to successfully conduct its essential
Assessing Enhanced Security Requirements for Controlled Unclassified Information
The protection of controlled unclassified information (CUI) resident in nonfederal systems and organizations is of paramount importance to federal agencies and can directly impact the ability of the Federal Government to successfully conduct its essential