Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/22309061. Does the introduction explain the objective of the research presented in the preprint? Partly The intro concisely lists the limitations of present methods used and but instead of listing their contributions, they mostly just vaguely go over it. Are the methods well-suited for this research? Somewhat appropriate Even though the methods used are well-suited and standard, they lack description. They do not completely explain how the volatge correction is applied, given that terminal voltage needs to relaxed before ocv vs soc calibration, no mention of how the rest works. In general, description is lacking and confusing. Are the conclusions supported by the data? Somewhat unsupported The conclusion is a bit over claimed. They only did cadence simulations of an otherwise complex system with batteries and actual sensors. The claims are a bit far reached and under supported. Are the data presentations, including visualizations, well-suited to represent the data? Somewhat inappropriate or unclear The figures are a bit low quality, making them hard to read and understand. How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Neither clearly nor unclearly They have some future works listed in general but they do not mention their next steps. Is the preprint likely to advance academic knowledge? Moderately likely Would it benefit from language editing? Yes The writing needs refining, specifically the claims need proper explaination and support. Would you recommend this preprint to others? Yes, but it needs to be improved Is it ready for attention from an editor, publisher or broader audience? No, it needs a major revision Competing interests The author declares that they have no competing interests. Use of Artificial Intelligence (AI) The author declares that they did not use generative AI to come up with new ideas for their review.
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
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.