Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
The ShowPapers Protocol keeps original documents, structured details, linked notes, organization and review decisions together in a portable collection. ZIP carries the files; the protocol defines their records, relationships, provenance and proposed changes. This technical report describes specification 1.0.0, including stable record identity, selected-snapshot exchange, reading/person/agent provenance, complete-collection imports, changes bound to an exact base, validation and an optional protected envelope. It explains exchanges with AI agents and the distinction between format conformance and application acceptance policy. The report also states the limits of checksums, provenance labels and encryption. The deposit includes the whitepaper and its editable LaTeX and Mermaid source bundle with pre-rendered figure PDFs. Reference documentation and tools are available at protocol.showpapers.app. Please cite this whitepaper and the relevant ShowPapers protocol version when using or building upon this work in software, research, technical publications, or patent applications. This citation request does not add conditions to the Apache License 2.0 or replace applicable patent-disclosure obligations.
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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