2 citations · 3 across the 3 of their papers we have counts for
5 papers
Evaluating and explaining training strategies for zero-shot cross-lingual news sentiment analysis
Luka Andrenšek, Boshko Koloski, Andraž Pelicon +3
We investigate zero-shot cross-lingual news sentiment detection, aiming to develop robust sentiment classifiers that can be deployed across multiple languages without target-langua…
AutoML-guided Fusion of Entity and LLM-based Representations for Document Classification
Boshko Koloski, Senja Pollak, Roberto Navigli +1
Large semantic knowledge bases are grounded in factual knowledge. However, recent approaches to dense text representations (i.e. embeddings) do not efficiently exploit these resour…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised?
Boshko Koloski, Senja Pollak, Blaž Škrlj +1
Keyword extraction is the task of retrieving words that are essential to the content of a given document. Researchers proposed various approaches to tackle this problem. At the top…
Identification of COVID-19 related Fake News via Neural Stacking
Boshko Koloski, Timen Stepišnik Perdih, Senja Pollak +1
Identification of Fake News plays a prominent role in the ongoing pandemic, impacting multiple aspects of day-to-day life. In this work we present a solution to the shared task tit…