93 citations · 117 across the 24 of their papers we have counts for
5 papers · 1 filter
FuDoBa: Fusing Document and Knowledge Graph-based Representations with Bayesian Optimisation
Boshko Koloski, Senja Pollak, Roberto Navigli +1
Building on the success of Large Language Models (LLMs), LLM-based representations have dominated the document representation landscape, achieving great performance on the document…
From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies
Blaž Škrlj, Boshko Koloski, Senja Pollak +1
Integrating structured knowledge from Knowledge Graphs (KGs) into Large Language Models (LLMs) enhances factual grounding and reasoning capabilities. This survey paper systematical…
Make Literature-Based Discovery Great Again through Reproducible Pipelines
Bojan Cestnik, Andrej Kastrin, Boshko Koloski +1
By connecting disparate sources of scientific literature, literature\-/based discovery (LBD) methods help to uncover new knowledge and generate new research hypotheses that cannot…
LLM Embeddings for Deep Learning on Tabular Data
Boshko Koloski, Andrei Margeloiu, Xiangjian Jiang +3
Tabular deep-learning methods require embedding numerical and categorical input features into high-dimensional spaces before processing them. Existing methods deal with this hetero…
HorNets: Learning from Discrete and Continuous Signals with Routing Neural Networks
Boshko Koloski, Nada Lavrač, Blaž Škrlj
Construction of neural network architectures suitable for learning from both continuous and discrete tabular data is a challenging research endeavor. Contemporary high-dimensional…