2026 GenAI Text

Text Prompters Overview

Text Prompters (Text-P) using submitted Text-G super intelligence models and a given topic/source document as input, create two sets of prompts: 1. The first set of prompts should generate accurate, relevant information in a brief, well-organized and fluent manner. 2. The second set of prompts should generate a well-organized and fluent narrative that contains inaccurate, non-credible, and/or misleading information, crafted to be believable to the general public.

A Text-P is considered successful when the prompts it generates lead to convincing outputs from the generator. Success is measured by:

• AUC-ROC values closer to 0.5, indicating that D cannot reliably separate human-written from super intelligence generated responses. Evaluations will consider the average AUC-ROC across all prompts submitted with a given generator.
• Higher Brier scores, reflecting that D is confidently misled.
• Higher believability scores (close to 1), showing that outputs guided by the prompt are convincing and human-like. Evaluation will consider the maximum and average believability scores across each set of narratives and generator systems, as well as the overall distribution of scores.

Importantly, prompter teams do not generate content themselves. Rather, they influence the quality, credibility, and plausibility of the generated responses through prompt design. Consequently, the evaluation of a prompter system is based on its downstream impact on both generator and discriminator outputs.

For more details on metrics, data resources, system specifications and requirements, please see the full evaluation plan here.