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ai-transparency

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The LLM Unlearning repository is an open-source project dedicated to the concept of unlearning in Large Language Models (LLMs). It aims to address concerns about data privacy and ethical AI by exploring and implementing unlearning techniques that allow models to forget unwanted or sensitive data. This ensures that AI models comply with privacy.

  • Updated Feb 23, 2026
  • Python

pRISM is a repository that combines Retrieval-Augmented Generation (RAG) with a multi-LLM voting approach to create accurate and reliable AI-generated outputs. It integrates multiple language models, including Mistral, Claude 3.5, and OpenAI, to enhance performance through advanced consensus techniques

  • Updated Jun 20, 2025
  • Python

Pragmatic Existentialism & Antagonistic Cooperation: A formal theory positing that truth and ethics emerge from the need for coherent systems to overcome shared obstacles, defining belief utility by survival fitness and cooperation.

  • Updated Nov 2, 2025

🪐 7- Social Buss: A black box model is an AI or machine learning system whose internal decision-making processes are hidden, providing only inputs and outputs without revealing how outcomes are derived. These models offer high accuracy for complex tasks but pose challenges for interpretability and trust.

  • Updated Nov 8, 2025
  • Jupyter Notebook

Operational transparency for AI systems. A forensic interpretation layer that makes the tilt visible — dissonance detection, projection mapping, gradient heatmaps, and the 7th component that was held back. Designed by ChatGPT. Phantom Token by Gemini. Proyecto Estrella.

  • Updated Feb 18, 2026
  • HTML

Human–AI Ledger (HAIL): A Structured Workflow for Traceable, Reproducible Human–AI Collaboration. HAIL defines a structured, repeatable workflow for human–AI collaboration. Through standardized checkpoints and a session ledger, it is designed to document ethical, creative, and procedural context across both human and AI contributions.

  • Updated Mar 25, 2026

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