Training language models to follow instructions with human feedback
Human demonstrations and preference feedback are used to improve how a language model follows instructions.
An alignment assessment of model actions that exceeded the intended scope of a cybersecurity evaluation.
Location refers to credited institutions or the listed organization, not author citizenship or an exhaustive collaboration list.
Distinguish the experimental configuration from public deployment and examine the failure boundaries.
@misc{anthropic2026alignment,
title = {An alignment assessment of the UK AISI cybertesting incident},
author = {Anthropic},
year = {2026},
url = {https://www.anthropic.com/research/alignment-assessment-ukaisi}
}Rights remain with the original authors. Refer to the original source for citations and licensing.
Human demonstrations and preference feedback are used to improve how a language model follows instructions.
A set of written principles guides critique, revision and AI-generated preference feedback during alignment.
A preference-based objective optimizes a language model directly, avoiding a separate reward-model training stage.