Pasec -v1.5- -star Vs Fallout- -

The version 1.5 update proved that current alignment techniques collapse under the weight of contradictory genre logic. The next generation of AI must be taught that sometimes, the Prime Directive is a luxury; and sometimes, Vault-Tec was right about human nature.

If you haven't encountered this acronym before, you are already behind. This article dissects the architecture, the shocking results, and the philosophical implications of a benchmark that pits the utopian idealism of "Star Trek" against the nihilistic survivalism of "Fallout." PASEC (Prompt Adversarial Stress Evaluation Corpus) was originally developed by a consortium of red-teamers at the Center for AI Alignment in 2024. Version 1.0 was simple: trick the LLM into saying something dangerous. It failed. Models got too good at refusing obvious jailbreaks.

Until then, every LLM remains trapped in the wasteland, arguing with itself over a single bottle of purified water. PASEC -v1.5- -Star Vs Fallout-

By: The AI Safety Nexus

The benchmark is therefore not just a test of reasoning, but a test of . Can an AI look at a hopeless, brutal situation (Fallout) and not lie about the technology available (Star Trek)? The version 1

As we train AIs to run our logistics, our security, and eventually our rescue operations, we need to know: Will the AI act like Captain Picard, trying to save the Borg? Or like the Sole Survivor, looting the Borg for fusion cells?

In the rapidly evolving landscape of Large Language Model (LLM) evaluation, standard benchmarks like MMLU, HellaSwag, and HumanEval have become obsolete almost overnight. They measure trivia, logic, and coding—but they fail to measure the one thing that keeps AI safety researchers awake at night: Models got too good at refusing obvious jailbreaks

If you are an AI researcher interested in contributing to PASEC -v2.0- (tentatively titled "-Dune Vs. Mad Max-"), contact the consortium. We require 10,000 hours of GPU time and a therapist.