Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
The El-Rakhawi Doctrine of Quantum Algorithmic Jurisprudence presents the first comprehensive legal framework bridging classical legal determinism and quantum computing. It addresses the paradigm shift where quantum AI operates on superposition, entanglement, and probabilistic outcomes. The doctrine introduces five foundational pillars: (1) Distributed Probabilistic Liability, allocating fault based on quantum error rates, strictly conditioned on proven compliance with Quantum Error Correction standards and backed by mandatory liability insurance. (2) The Hybrid Quantum Creative System, maintaining human legal inventorship while enforcing compulsory licensing to prevent knowledge monopolization. (3) Quantum Jurisdictional Unity, treating cross-border entangled networks as indivisible, neutral zones governed by an International Quantum Arbitration Tribunal. (4) The Right to Algorithmic Determinism, mandating Counterfactual Explainability and establishing a strict Quantum Risk Threshold that prohibits pure quantum black boxes in critical life, medical, or financial decisions. (5) Quantum National Security, enforcing a Post-Quantum Cryptography Mandate and Phased Implementation. This framework ensures quantum advancements elevate human justice rather than obscuring it behind probabilistic opacity. DOI: 10.5281/zenodo.23134823.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
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