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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

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Showing 2024Show all

6 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★ 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…