Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Academic Publishing and Open Access
Abstract
Twenty years after open access transformed scholarly publishing, another game-changer in the form of generative AI emerged, bringing with it significant implications for the quality of the scholarly record. The peer-review system, which has long been the most important gatekeeping and evaluation mechanism used by publishers, is challenged by reviewer fatigue and shortages and now faces additional pressure from AI-enabled research integrity violations and AI-generated peer reviews. Drawing on data from 47 qualitative interviews conducted with publishers and publishing-adjacent stakeholders, this poster presents insights into how AI has affected editorial quality mechanisms across the industry. In this context, academic publishers are split into two groups: Smaller- and mid-sized presses that mainly rely on peer review for quality control as AI tools are lacking. Large publishing houses that supplement peer review with AI-powered software to help identify and address research integrity issues stemming from AI (ab)use. For publishers, access to AI-detection tools – or the lack thereof – will have long-term effects on the quality of the scholarly record, which may also impact the academic publishing ecosystem in the future. The two-pronged discussion question becomes: what does review-based gatekeeping look like in the age of AI, and how can all publishers, together with the scholarly community, ensure that the quality of their publications is preserved?
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
Related blog posts
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
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.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.