Oct 2026· ACM/IEEE Joint Conference on Digital Libraries· 2 references
Digital and Traditional Archives Management
Abstract
The Software Heritage (SWH) archive pursues the monumental mission of preserving the world’s software source code. However, the advent of generative AI has triggered an AI Code Explosion, exponentially accelerating the production of synthesized code and leading to severe storage capacity challenges. As preserving the entirety of global source code indefinitely presents an increasing physical and economic challenge for decentralized mirror servers, complementary strategies for archival prioritization become a valuable consideration. This poster introduces the Universal Value Index (UVI), a highly scalable, graph-topological heuristic model designed to quantify the “Outstanding Universal Value” of software repositories to assist in decentralized capacity planning. Inspired by established UNESCO World Heritage criteria, the UVI evaluates repositories across four dimensions: Impact, Time, Rarity, and Quality, alongside specific penalizations for redundant forks and data bloat. While determining objective value is intrinsically challenging, our preliminary goal is to provide a consistent and transparent first-step prioritization for archiving. By offering a mathematical framework mapped to cultural heritage standards, the UVI enables digital archivists to make scalable triage decisions to help secure critical digital infrastructure.
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
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026