140 citations · 293 across the 12 of their papers we have counts for
13 papers
The Labeling Problem in Hallucination Detection Benchmarks: An Empirical Evaluation
Jorma Valjakka, Juhani Kivimäki, Juha Mylläri +1
In recent years, several methods for detecting when large language models (LLMs) hallucinate have been developed. These methods are often benchmarked with open-domain question answ…
The Impact of Feature Embedding Placement in the Ansatz of a Quantum Kernel in QSVMs
Ilmo Salmenperä, Ilmars Kuhtarskis, Arianne Meijer van de Griend +1
Designing a useful feature map for a quantum kernel is a critical task when attempting to achieve an advantage over classical machine learning models. The choice of circuit archite…
Confidence-based Estimators for Predictive Performance in Model Monitoring
Juhani Kivimäki, Jakub Białek, Jukka K. Nurminen +1
After a machine learning model has been deployed into production, its predictive performance needs to be monitored. Ideally, such monitoring can be carried out by comparing the mod…
Quantum Software Engineering Challenges from Developers' Perspective: Mapping Research Challenges to the Proposed Workflow Model
Majid Haghparast, Tommi Mikkonen, Jukka K. Nurminen +1
Despite the increasing interest in quantum computing, the aspect of development to achieve cost-effective and reliable quantum software applications has been slow. One barrier is t…
On Misbehaviour and Fault Tolerance in Machine Learning Systems
Lalli Myllyaho, Mikko Raatikainen, Tomi Männistö +2
Machine learning (ML) provides us with numerous opportunities, allowing ML systems to adapt to new situations and contexts. At the same time, this adaptability raises uncertainties…
Systematic Literature Review of Validation Methods for AI Systems
Lalli Myllyaho, Mikko Raatikainen, Tomi Männistö +2
Context: Artificial intelligence (AI) has made its way into everyday activities, particularly through new techniques such as machine learning (ML). These techniques are implementab…