20 citations · 31 across the 3 of their papers we have counts for
4 papers
CERN for AI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment
Ljubisa Bojic, Matteo Cinelli, Dubravko Culibrk +1
This paper explores the potential of a multidisciplinary approach to testing and aligning artificial intelligence (AI), specifically focusing on large language models (LLMs). Due t…
Tabular Few-Shot Generalization Across Heterogeneous Feature Spaces
Max Zhu, Katarzyna Kobalczyk, Andrija Petrovic +4
Despite the prevalence of tabular datasets, few-shot learning remains under-explored within this domain. Existing few-shot methods are not directly applicable to tabular datasets d…
Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models
Aleksa Bisercic, Mladen Nikolic, Mihaela van der Schaar +3
Tabular data is often hidden in text, particularly in medical diagnostic reports. Traditional machine learning (ML) models designed to work with tabular data, cannot effectively pr…
Gaussian Conditional Random Fields for Classification
Andrija Petrović, Mladen Nikolić, Miloš Jovanović +1
Gaussian conditional random fields (GCRF) are a well-known used structured model for continuous outputs that uses multiple unstructured predictors to form its features and at the s…