activity
20202026
most citedSkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification

3 citations · 17 across the 45 of their papers we have counts for

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Showing 2024Show all

10 papers · 1 filter

cs.CL2024

RoLargeSum: A Large Dialect-Aware Romanian News Dataset for Summary, Headline, and Keyword Generation

Andrei-Marius Avram, Mircea Timpuriu, Andreea Iuga +6

Using supervised automatic summarisation methods requires sufficient corpora that include pairs of documents and their summaries. Similarly to many tasks in natural language proces…

cs.CL2024

GRAF: Graph Retrieval Augmented by Facts for Romanian Legal Multi-Choice Question Answering

Cristian-George Crăciun, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel +1

Pre-trained Language Models (PLMs) have shown remarkable performances in recent years, setting a new paradigm for NLP research and industry. The legal domain has received some atte…

cs.CL2024★ 1 cited

Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain Setups

Răzvan-Alexandru Smădu, David-Gabriel Ion, Dumitru-Clementin Cercel +2

Complex Word Identification (CWI) is an essential step in the lexical simplification task and has recently become a task on its own. Some variations of this binary classification t…

cs.CL2024

A Cross-Lingual Meta-Learning Method Based on Domain Adaptation for Speech Emotion Recognition

David-Gabriel Ion, Răzvan-Alexandru Smădu, Dumitru-Clementin Cercel +2

Best-performing speech models are trained on large amounts of data in the language they are meant to work for. However, most languages have sparse data, making training models chal…

cs.CL2024

RoQLlama: A Lightweight Romanian Adapted Language Model

George-Andrei Dima, Andrei-Marius Avram, Cristian-George Crăciun +1

The remarkable achievements obtained by open-source large language models (LLMs) in recent years have predominantly been concentrated on tasks involving the English language. In th…

cs.CL2024★ 1 cited

Enhancing Romanian Offensive Language Detection through Knowledge Distillation, Multi-Task Learning, and Data Augmentation

Vlad-Cristian Matei, Iulian-Marius Tăiatu, Răzvan-Alexandru Smădu +1

This paper highlights the significance of natural language processing (NLP) within artificial intelligence, underscoring its pivotal role in comprehending and modeling human langua…

cs.CL2024

Investigating the Impact of Semi-Supervised Methods with Data Augmentation on Offensive Language Detection in Romanian Language

Elena-Beatrice Nicola, Dumitru-Clementin Cercel, Florin Pop

Offensive language detection is a crucial task in today's digital landscape, where online platforms grapple with maintaining a respectful and inclusive environment. However, buildi…

cs.CL2024★ 2 cited

HistNERo: Historical Named Entity Recognition for the Romanian Language

Andrei-Marius Avram, Andreea Iuga, George-Vlad Manolache +8

This work introduces HistNERo, the first Romanian corpus for Named Entity Recognition (NER) in historical newspapers. The dataset contains 323k tokens of text, covering more than h…

cs.CV2024★ 1 cited

Explainability-Driven Leaf Disease Classification Using Adversarial Training and Knowledge Distillation

Sebastian-Vasile Echim, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel +1

This work focuses on plant leaf disease classification and explores three crucial aspects: adversarial training, model explainability, and model compression. The models' robustness…

cs.CV2024★ 1 cited

Evaluating Data Augmentation Techniques for Coffee Leaf Disease Classification

Adrian Gheorghiu, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel +2

The detection and classification of diseases in Robusta coffee leaves are essential to ensure that plants are healthy and the crop yield is kept high. However, this job requires ex…