Agent-based modeling (ABM) is a powerful tool for simulating building users’ dynamic behavior in demand response (DR) programs. However, ABM faces several challenges, particularly in encoding building users’ natural language features and common sense into rules or mathematical equations. To overcome …

Artificial Intelligence (AI) is transforming workflows across various industries, including life sciences. When deployed securely, generative AI tools can automate structured programming tasks. In clinical research, a significant challenge is converting raw trial data into the formats required for regulatory …

This paper presents a generative large language model (LLM)- guided approach to detect discursive patterns in Dutch social media.

Deze presentatie neemt je mee in de basisarchitectuur van Large Language Models en laat zien hoe Fenna Feenstra en Wynand Alkema samen met studenten een BERT‑model hebben ontwikkeld om longceltypes te annoteren. Ten slotte bespreken ze de bredere impact van LLM’s op het vakgebied en de kansen die ze …

There are many good reasons to use synthetic data instead of real data for research purposes. These reasons may range from the business sensitiveness of real data to increased cost of collecting real data in accordance with GDPR requirements. In this paper, we elaborate upon the potentials of the Large …

We present our ongoing work on upgrading the Amsterdam Public Library's book database search capabilities. So far, users have had to input the exact book title and/or author name without any typos or misspellings in order to retrieve any results. This is in sharp contrast with the manner in which users …

To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes …

The recent advancements in machine learning (ML) techniques have significantly improved the performance in various natural language processing (NLP) tasks, particularly in deep learning with the transformer architecture. Despite their promising applications in different domains, these innovations have …

With the proliferation of misinformation on the web, automatic methods for detecting misinformation are becoming an increasingly important subject of study. If automatic misinformation detection is applied in a real-world setting, it is necessary to validate the methods being used. Large language models …

In this paper, we examine to what degree children of 3–4 years old engage with a task and with a social robot during a second-language tutoring lesson. We specifically investigated whether children’s task engagement and robot engagement were influenced by three different feedback types by the robot: …