activity
20232025
most citedExplainability-Driven Leaf Disease Classification Using Adversarial Training and Knowledge Distillation

1 citations · 4 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2025★ 1 cited

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…

cs.CY2025

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…

cs.CV2025

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…

cs.CL2025

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…

cs.CL2025

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…

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★ 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

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.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…

cs.CV2023

End-to-End Lip Reading in Romanian with Cross-Lingual Domain Adaptation and Lateral Inhibition

Emilian-Claudiu Mănescu, Răzvan-Alexandru Smădu, Andrei-Marius Avram +2

Lip reading or visual speech recognition has gained significant attention in recent years, particularly because of hardware development and innovations in computer vision. While co…