Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
This collection preserves P. G. Lejeune Dirichlet’s mathematical works as original-language working transcriptions, English translations, editable LaTeX, source scans and checking records. Its established core is Werke Band II Papers I–XLI, including the cumulative readers, component sources, correspondence, notices and the R23 correction and repair material. Band I source staging and the historical R27/R28 Paper IV packages are also retained. The collection has mixed editorial status. The Band II readers remain working drafts: Paper XXV still needs complete formula-level repair, and Paper XXVII still needs a typed German source track. Older selected or partial drafts and the retained Public Summary describe historical states. They must not be treated as complete, accuracy-certified editions. The R23 warnings and source witnesses remain part of the collection. Edition update — 21 September 2026. Band I Paper IV, Recherches sur les diviseurs premiers d’une classe de formules du quatrième degré, is now available in complete French and English readers, each covering all 34 author pages 65–98 of the 1889 collected witness. Title and blank leaves 63–64 are preserved separately; Paper V is excluded. A five-page apparatus records printed anomalies without silently repairing the author text. The complete edition archive includes every editable page, the full and scoped source scans, inherited material, page-by-page audit evidence, correction snapshots and build sources. These readers supersede the partial R27/R28 reading coverage for Paper IV; those older packages remain as provenance. Dirichlet is the author of the mathematics. The modern transcription and translation are AI-assisted: ChatGPT Pro compared the text with source images and performed a fresh final source pass; Codex checked the full return, source and repair bindings, rebuilt the readers, compared their text and inspected all 73 rendered pages. This is not independent human peer review or a critical edition across witnesses. Completion applies to Paper IV alone, not either collected volume. Read the Paper IV English PDF in the preview, or choose the French reader and apparatus in the file list. The edition guide explains the current and retained files. Corrections and source comparisons can be proposed through https://github.com/KokunoYumeto/modern-latex-manuscripts. The stable collection identifier is https://doi.org/10.5281/zenodo.20520679.
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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