1 citations · 3 across the 7 of their papers we have counts for
7 papers
Text2Graph: Combining Lightweight LLMs and GNNs for Efficient Text Classification in Label-Scarce Scenarios
João Lucas Luz Lima Sarcinelli, Ricardo Marcondes Marcacini
Large Language Models (LLMs) have become effective zero-shot classifiers, but their high computational requirements and environmental costs limit their practicality for large-scale…
OLGA: One-cLass Graph Autoencoder
M. P. S. Gôlo, J. G. B. M. Junior, D. F. Silva +1
One-class learning (OCL) comprises a set of techniques applied when real-world problems have a single class of interest. The usual procedure for OCL is learning a hypersphere that…
Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment Analysis
Guilherme Lourenço de Toledo, Ricardo Marcondes Marcacini
Most existing methods focus on sentiment analysis of textual data. However, recently there has been a massive use of images and videos on social platforms, motivating sentiment ana…
Semi-Supervised Graph Attention Networks for Event Representation Learning
Joao Pedro Rodrigues Mattos, Ricardo M. Marcacini
Event analysis from news and social networks is very useful for a wide range of social studies and real-world applications. Recently, event graphs have been explored to model event…
BULNER: BUg Localization with word embeddings and NEtwork Regularization
Jacson Rodrigues Barbosa, Ricardo Marcondes Marcacini, Ricardo Britto +4
Bug localization (BL) from the bug report is the strategic activity of the software maintaining process. Because BL is a costly and tedious activity, BL techniques information retr…
Evaluation of Classifiers for Image Segmentation: Applications for Eucalypt Forest Inventory
Rodrigo M. Ferreira, Ricardo M. Marcacini
The task of counting eucalyptus trees from aerial images collected by unmanned aerial vehicles (UAVs) has been frequently explored by techniques of estimation of the basal area, i.…
Combining Privileged Information to Improve Context-Aware Recommender Systems
Camila V. Sundermann, Marcos A. Domingues, Ricardo M. Marcacini +1
A recommender system is an information filtering technology which can be used to predict preference ratings of items (products, services, movies, etc) and/or to output a ranking of…