3 citations · 17 across the 45 of their papers we have counts for
12 papers · 1 filter
Parameter Efficient Multimodal Instruction Tuning for Romanian Vision Language Models
George-Andrei Dima, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel
Focusing on low-resource languages is an essential step toward democratizing generative AI. In this work, we contribute to reducing the multimodal NLP resource gap for Romanian. We…
RoCoISLR: A Romanian Corpus for Isolated Sign Language Recognition
Cătălin-Alexandru Rîpanu, Andrei-Theodor Hotnog, Giulia-Stefania Imbrea +1
Automatic sign language recognition plays a crucial role in bridging the communication gap between deaf communities and hearing individuals; however, most available datasets focus…
Air Pollution Forecasting in Bucharest
Dragoş-Andrei Şerban, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel
Air pollution, especially the particulate matter 2.5 (PM2.5), has become a growing concern in recent years, primarily in urban areas. Being exposed to air pollution is linked to de…
SeLeRoSa: Sentence-Level Romanian Satire Detection Dataset
Răzvan-Alexandru Smădu, Andreea Iuga, Dumitru-Clementin Cercel +1
Satire, irony, and sarcasm are techniques typically used to express humor and critique, rather than deceive; however, they can occasionally be mistaken for factual reporting, akin…
Multimodal Learning with Augmentation Techniques for Natural Disaster Assessment
Adrian-Dinu Urse, Dumitru-Clementin Cercel, Florin Pop
Natural disaster assessment relies on accurate and rapid access to information, with social media emerging as a valuable real-time source. However, existing datasets suffer from cl…
MoRoVoc: A Large Dataset for Geographical Variation Identification of the Spoken Romanian Language
Andrei-Marius Avram, Ema-Ioana Bănescu, Anda-Teodora Robea +2
This paper introduces MoRoVoc, the largest dataset for analyzing the regional variation of spoken Romanian. It has more than 93 hours of audio and 88,192 audio samples, balanced be…
IGAff: Benchmarking Adversarial Iterative and Genetic Affine Algorithms on Deep Neural Networks
Sebastian-Vasile Echim, Andrei-Alexandru Preda, Dumitru-Clementin Cercel +1
Deep neural networks currently dominate many fields of the artificial intelligence landscape, achieving state-of-the-art results on numerous tasks while remaining hard to understan…
RoD-TAL: A Benchmark for Answering Questions in Romanian Driving License Exams
Andrei Vlad Man, Răzvan-Alexandru Smădu, Cristian-George Craciun +3
The intersection of AI and legal systems presents a growing need for tools that support legal education, particularly in under-resourced languages such as Romanian. In this work, w…
MuSaRoNews: A Multidomain, Multimodal Satire Dataset from Romanian News Articles
Răzvan-Alexandru Smădu, Andreea Iuga, Dumitru-Clementin Cercel
Satire and fake news can both contribute to the spread of false information, even though both have different purposes (one if for amusement, the other is to misinform). However, it…
Scaling Federated Learning Solutions with Kubernetes for Synthesizing Histopathology Images
Andrei-Alexandru Preda, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel
In the field of deep learning, large architectures often obtain the best performance for many tasks, but also require massive datasets. In the histological domain, tissue images ar…
SaRoHead: Detecting Satire in a Multi-Domain Romanian News Headline Dataset
Mihnea-Alexandru Vîrlan, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel +2
The primary goal of a news headline is to summarize an event in as few words as possible. Depending on the media outlet, a headline can serve as a means to objectively deliver a su…
UniBERT: Adversarial Training for Language-Universal Representations
Andrei-Marius Avram, Marian Lupaşcu, Dumitru-Clementin Cercel +2
This paper presents UniBERT, a compact multilingual language model that uses an innovative training framework that integrates three components: masked language modeling, adversaria…