We use GPT-4 for content policy development and content moderation decisions, enabling more consistent labeling, a faster feedback loop for policy refinement, and less involvement from human moderators.
We’re introducing a new model built on GPT-4o that is more accurate at detecting harmful text and images, enabling developers to build more robust moderation systems.
We are introducing a new and improved content moderation tool. The Moderation endpoint improves upon our previous content filter, and is available for free today to OpenAI API developers.
It can generate, edit, and iterate with users on creative and technical writing tasks, such as composing songs, writing screenplays, or learning a user’s writing style.
arXiv:2609.10410v1 Announce Type: new Abstract: The growing complexity of content moderation policies presents a critical challenge for their consistent operationalization. While foundation models po...
Ironclad uses GPT-4 to simplify the contract review process.
The paper introduces DECO, a diagnostic tool that factorises content into independent criteria for evaluating large language models (LLMs) on content moderation tasks. Using DECO and pairwise evaluation across four datasets and four LLMs, the authors find that high benchmark scores can mask significant failures at the criterion level, especially when decisions hinge on specific content aspects rather than overall harmfulness. The study underscores that aggregated label performance does not guarantee reliable criterion-conditioned evaluation, calling for new methods that explicitly assess this behavior.
The paper introduces DECO, a diagnostic framework that factorises content into independent moderation criteria, allowing controlled evaluation of large language models (LLMs) at the criterion level. Using pairwise evaluation across four datasets and four LLMs, the authors find that high aggregate benchmark scores can mask significant failures when decisions hinge on specific content aspects required by individual criteria. The study underscores that aggregated labels do not guarantee reliable criterion-conditioned performance, highlighting the need for evaluation methods that explicitly assess this behavior.
Altera uses GPT-4o to build a new area of human collaboration
GPT-5. 5 Instant updates ChatGPT’s default model with smarter, more accurate answers, reduced hallucinations, and improved personalization controls.