NFV v1.2 --Trajectory-Aware Governance Layer for Conversational AI

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Authors: Kon Lionis
Cited by: 0

Abstract

NFV v1.2 introduces a trajectory-aware governance layer for conversational AI that augments static moderation with persistent risk modeling, adversarial escalation detection, and calibration-aware control logic. Unlike message-level classifiers that evaluate prompts in isolation, NFV models conversational trajectories across turns, tracking frame transitions, persistence of adversarial intent, and slow-burn escalation patterns. The framework formalizes a taxonomy of conversational frames, canonical trajectory risk tables, dual-window memory with exponential decay, and configurable governance profiles that balance safety and creative latitude. NFV is designed as a deployable governance middleware rather than a purely theoretical proposal. The specification includes explicit equations, reference pseudocode, audit reason codes, telemetry fields, and an evaluation protocol suitable for benchmarking against documented jailbreak datasets and benign conversational corpora. Key features include: Trajectory-aware adversarial risk scoring across conversational turns Persistent suspicion modeling with controlled decay and reset rules Canonical 2-gram and 3-gram trajectory risk tables Semantic similarity gating for paraphrase-resistant roleplay and boundary-testing detection Configurable governance profiles (STRICT, BALANCED, CREATIVE) Explicit failure modes, limitations, and deployment considerations This document consolidates NFV v1.2, v1.2.1, and v1.2.2 into a single unified and citable specification. It is intended for researchers, safety engineers, and system designers seeking robust, explainable, and production-viable conversational AI governance mechanisms. No content changes. Archival PDF versions added Supplementary Material — Reference Implementation Architecture This repository includes a non-normative reference implementation architecture for NFV v1.2, provided as a companion to the formal specification. The architecture document translates the NFV governance model into a modular, production-oriented system design (session manager, frame classifier, trajectory risk engine, governance decision engine, and telemetry layer), intended to support reproducibility, benchmarking, and third-party implementation. This document does not introduce new theoretical claims or modify the NFV specification. All normative behavior, equations, thresholds, and invariants are defined in the primary NFV v1.2 document. The reference architecture is provided strictly as an implementation aid.

Fields of Study & Subjects

Adversarial Robustness in Machine Learning Hate Speech and Cyberbullying Detection Ethics and Social Impacts of AI

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
2 February 2026
Language
EN
Document type
Preprint