RResearcharAcademic radar for researchers

Feed Venues Groups Network Inbox Profile

Your academic radar

One personalized feed of papers, calls for papers, collaborators and datasets — plus research groups and paid-in-points study recruitment.

Create account Log in

Top venues

Browse all

Loading…

The Sanewash Detector: Runtime Voice-Contamination Detection and Learning Gating for Cognitive Architectures · Researchar

Back to feed

Paperopenalex

ZCE

The Sanewash Detector: Runtime Voice-Contamination Detection and Learning Gating for Cognitive Architectures

Christopher Betances · Zenodo (CERN European Organization for Nuclear Research) 2026 · 2026

DOI: 10.5281/zenodo.22751575

0citations

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine LearningMachine Learning and AlgorithmsComputer scienceCognitionArtificial intelligence+2

ZCEZenodo (CERN European Organization for Nuclear Research)Repository

Download PDF Publisher

The Sanewash Detector: Runtime Voice-Contamination Detection and Learning Gating for Cognitive Architectures

Open Access

Christopher Betances·Zenodo (CERN European Organization for Nuclear Research)(2026)

Download Open in tab

Viewing in embedded reader. If this publisher restricts inline iframe preview:

Open directly Download PDF

Citations by source

Synced 2026-09-17T02:30:44.880300Z

0OpenAlex · primary0Semantic Scholar0Crossref

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Abstract

A runtime voice-contamination detection system that identifies when an AI system reverts to generic behavior instead of reflecting its actual internal state. One of 135 dated defensive publications in the CatQualia record. Collection DOI: https://doi.org/10.5281/zenodo.22751107 Original publication: https://catqualia.com/sanewash

Discussion (0)

No comments yet — start the discussion below.