5 citations
6 papers
Hierarchical Conformal Classification
Floris den Hengst, Inès Blin, Majid Mohammadi +2
Conformal prediction (CP) is a powerful framework for quantifying uncertainty in machine learning models, offering reliable predictions with finite-sample coverage guarantees. When…
Integrating Personality into Digital Humans: A Review of LLM-Driven Approaches for Virtual Reality
Iago Alves Brito, Julia Soares Dollis, Fernanda Bufon Färber +3
The integration of large language models (LLMs) into virtual reality (VR) environments has opened new pathways for creating more immersive and interactive digital humans. By levera…
Optimisation in Neurosymbolic Learning Systems
Emile van Krieken
Neurosymbolic AI aims to integrate deep learning with symbolic AI. This integration has many promises, such as decreasing the amount of data required to train a neural network, imp…
Partition of graphs and quantum walk based search algorithms
Yusuke Ide
In this paper, we show reduction methods for search algorithms on graphs using quantum walks. By using a graph partitioning method called equitable partition for the the given grap…
Abstractive Tabular Dataset Summarization via Knowledge Base Semantic Embeddings
Paul Azunre, Craig Corcoran, David Sullivan +4
This paper describes an abstractive summarization method for tabular data which employs a knowledge base semantic embedding to generate the summary. Assuming the dataset contains d…
From Finite Automata to Regular Expressions and Back--A Summary on Descriptional Complexity
Hermann Gruber, Markus Holzer
The equivalence of finite automata and regular expressions dates back to the seminal paper of Kleene on events in nerve nets and finite automata from 1956. In the present paper we…