Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Cognitive Computing and Networks
Abstract
The LIL V.6 Prespatial Chronogeometry Engineering Computing Module represents the next conceptual stage in the evolution of the LIL Quantum DSL family. Building on the non‑binary impulse logic of LIL V.3 and the semantic compression framework of LIL V.4, LIL V.6 introduces a unified temporal–semantic layer designed for modern AI latent spaces. This public academic edition presents the high‑level mathematical and conceptual principles behind temporal coherence, semantic geometry, identity preservation, and latent‑space evolution. Temporal behavior is treated as an intrinsic structural property of semantic constructs, enabling coherent progression, stable identity, and predictable transitions across generative processes. The document outlines how semantic and temporal dimensions can coexist within compressed latent representations, forming a continuous lineage: LIL V.3 → LIL V.4 → LIL V.5 → LIL V.6. All engineering‑level mechanisms, operators, and theoretical implementation details remain protected and are available exclusively under NDA. This edition serves as a safe, academically transparent reference for future research into structured temporal behavior within AI systems.
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
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
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
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