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Active learning (AL) has demonstrated remarkable potential in reducing the annotation effort required for training machine learning models. However, despite the surging popularity of natural language generation (NLG) tasks in recent years,…
The rapid evolution of generative AI has expanded the breadth of risks associated with AI systems. While various taxonomies and frameworks exist to classify these risks, the lack of interoperability between them creates challenges for…
The scientific system that we use today was devised centuries ago and is inadequate for our current ICT-based society: the peer review system encourages conservatism, journal publications are monolithic and slow, data is often not available…
Geoff is a collection of Python packages that form a framework for automation of particle accelerator controls. With particle accelerator laboratories around the world researching machine learning techniques to improve accelerator…
Collaborative group projects are integral to computer science education, fostering teamwork, problem-solving, and industry-relevant skills. However, assessing individual contributions within group settings remains challenging. Traditional…
This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing…
The ATLAS detector at CERN has completed its first full year of recording collisions at 7 TeV, resulting in billions of events and petabytes of data. At these scales, physicists must have the capability to read only the data of interest to…
Multi-agent Large Language Model (LLM) systems have been leading the way in applied LLM research across a number of fields. One notable area is software development, where researchers have advanced the automation of code implementation,…
Despite a growing ecosystem of tools supporting Systematic Literature Reviews (SLRs), integrating them into user-friendly workflows remains challenging. The Streamlined Workflow for Automating Machine-Actionable Systematic Literature…
In the field of scientific computing, one often finds several alternative software packages (with open or closed source code) for solving a specific problem. These packages sometimes even use alternative methodological approaches, e.g.,…
This paper presents a new Python library called Automated Learning for Insightful Comparison and Evaluation (ALICE), which merges conventional feature selection and the concept of inter-rater agreeability in a simple, user-friendly manner…
Autonomous editorial systems represent an emerging class of computational frameworks that transform how large volumes of information are ingested, organized, and analyzed. This work presents a structured, continuously operating editorial…
Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere knowledge and data have surpassed human analytical capacity.…
Trustworthy language models should provide both correct and verifiable answers. However, citations generated directly by standalone LLMs are often unreliable. As a result, current systems insert citations by querying an external retriever…
The automation of scientific discovery represents a critical milestone in Artificial Intelligence (AI) research. However, existing agentic systems for science suffer from two fundamental limitations: rigid, pre-programmed workflows that…
The increasing risk of epidemics and a fast-growing world population has contributed to a great investment in phylogenetic analysis, in order to track numerous diseases and conceive effective medication and treatments. Phylogenetic analysis…
Intelligent systems for the annotation of media content are increasingly being used for the automation of parts of social science research. In this domain the problem of integrating various Artificial Intelligence (AI) algorithms into a…
Automated intrusion-style workflows require LLM agents to reason over partial observations, tool outputs, and executable artifacts under bounded budgets. A single LLM instance often compresses evidence extraction, planning, execution, and…
We present RCE (Remote Component Environment), an open-source framework developed primarily at DLR (German Aerospace Center) that enables its users to construct and execute multidisciplinary engineering workflows comprising multiple…
Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for…