93 citations · 117 across the 24 of their papers we have counts for
6 papers · 1 filter
SEKE: Specialised Experts for Keyword Extraction
Matej Martinc, Hanh Thi Hong Tran, Senja Pollak +1
Keyword extraction involves identifying the most descriptive words in a document, allowing automatic categorisation and summarisation of large quantities of diverse textual data. R…
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…
A Computational Analysis of the Dehumanisation of Migrants from Syria and Ukraine in Slovene News Media
Jaya Caporusso, Damar Hoogland, Mojca Brglez +3
Dehumanisation involves the perception and or treatment of a social group's members as less than human. This phenomenon is rarely addressed with computational linguistic techniques…
Multi-Task Learning for Features Extraction in Financial Annual Reports
Syrielle Montariol, Matej Martinc, Andraž Pelicon +4
For assessing various performance indicators of companies, the focus is shifting from strictly financial (quantitative) publicly disclosed information to qualitative (textual) info…