large language models

TD-interpreter: enhancing the understanding of timing diagrams with visual-language learning

Abstract We introduce TD-Interpreter, a specialised machine learning (ML) workflow that assists engineers in understanding complex timing diagrams (TDs), originating from a third party, during their design and verification process. The outcome of this workflow is a visual question-answer environment which allows engine...

Data Optimization for LLMs: A Survey

Large language models (LLMs) have attracted great attention in both academic and industrial communities in recent years. Numerous survey studies have covered various aspects of LLMs, such as learning strategies, applications, alignment, explainability, and evaluation. However, little headway has been made in reviewing...

Representative Social Choice: From Learning Theory to AI Alignment

Social choice theory is the study of preference aggregation across a population, used both in mechanism design for human agents and in the democratic alignment of language models. In this study, we propose the representative social choice framework for the modeling of democratic representation in collective decisions,...

Does the additional attraction of a dwarf galaxy depend on its history? A pre-registered test of the quenching-time relation on 51 dwarf galaxies

Does the additional attraction of a dwarf galaxy depend on its history? A pre-registered test of the quenching-time relation on 51 dwarf galaxies. Version 1.5, 16 October 2026. The Informational Vector World Model (IVW) predicts that dwarf galaxies which stopped forming stars early show a larger velocity dispersion tha...

Usability Analysis of Configurator User Interfaces with Multimodal Large Language Models

AI-Enabled Cognitive Rehabilitation Robot

This paper presents an AI-enabled Cognitive Rehabilitation Robot designed to support people with cognitive disorders through natural and accessible interaction. The prototype integrates computer vision, natural language processing (NLP), and a large language model (LLM) using a Raspberry Pi 5 as its main processing uni...

Efficient and Effective Test Generation and Type Inference for Python Applications

Python has become one of the most widely used programming languages, valued for its flexibility and ease of use. However, its dynamic nature provides only limited static guarantees, making programs more difficult to write reliably: errors are more likely to remain undetected until runtime. Tests and type checking can m...

Compact Reinforcement Learning: Resource-Efficient Formulations for Large-Scale Decision Making

Reinforcement learning (RL) offers a general framework for addressing problems involving sequential decision-making. However, modern practical applications of RL involve prohibitively large state and action sets: such as those in slate recommendations, image-based control, and large language-modeling tasks. Standard fo...

MAOMAO: an ontology-guided FAIR resource for harmonized peptide toxicity data

Therapeutic peptides have emerged as a rapidly expanding class of biomolecules with applications spanning antimicrobial, antiviral, anticancer, immunomodulatory, metabolic, and diagnostic settings (8). Their high target specificity, favorable safety profiles, and growing clinical success have positioned them as attract...

Behavioral Analysis of AI-Assisted User Interaction in a Digital Art Repository

Recent developments in artificial intelligence, including the emergence of generative AI and large language models, have brought changes to user interaction habits as well as interface design. These emerging technologies can be integrated into digital art repositories to reshape interaction paradigms through content en...

Cloud‐Native and Distributed Systems for Efficient and Scalable Large Language Models—A Research Agenda

ABSTRACT Objective Large Language Models (LLMs) are rapidly transforming artificial intelligence applications, but their unprecedented computational, memory, communication, and data‐management demands pose significant challenges to existing computing infrastructures. Traditional cloud and distributed systems were not d...

Protocol: From Pilots to Practice: A Scoping Review of Artificial Intelligence Adoption in the Healthcare Sector of the GCC Countries and Egypt

Protocol (version 0.6, 17 October 2026) for a scoping review mapping the adoption of artificial intelligence across five healthcare sectors in Saudi Arabia, the United Arab Emirates, Qatar, Kuwait, Bahrain, Oman and Egypt (2015–2026): hospitals and providers; pharmaceutical companies and manufacturers; pharmacies and d...