Associative Tokenized Memory Architecture for Testing Behavioral Response in Large Language Models (New Release OMEN)

📖 Description: OMEN (Enhanced-ATP v3.0) introduces the revolutionary Associative Tokenized Memory Architecture (ATMA), designed to enhance behavioral response testing in large language models. This improved version significantly boosts context retention, adaptive learning, and dynamic response capabilities. The architecture leverages associative memory principles to maintain continuity and depth in interactions, making it an ideal tool for testing and analyzing advanced conversational behaviors. Users can explore the foundational mechanisms of associative memory and evaluate its real-time application within controlled environments. This release on Zenodo marks the first phase of our broader implementation strategy, aiming to make the system widely accessible for testing, research, and further development. 🛡️ License: This project is distributed under a multi-license protection stack: Creative Commons BY-NC-SA 4.0 — open for research and educational usehttps://creativecommons.org/licenses/by-nc-sa/4.0/ CC BNNC Kagata Clause — restricts misuse in surveillance, military, or behavior-modifying systems MIT License (fallback) — applies only to non-commercial code integration 🪪 Author: Bato NaidanovCopyright Registration No. 1-14916778941DOI: 10.5281/zenodo.15320954 10.5281/zenodo.15377514 Telegram: @BATONAIDANOV 🔏 Legal Note: All symbolic logic and activation structures are protected by publication timestamp, registered copyright, and DOI.This release supersedes earlier unpublished drafts and informal versions sent to institutions.Any derivative work must preserve symbolic integrity and attribution.