Papers with Romanian language

11 papers
A Novel Cartography-Based Curriculum Learning Method Applied on RoNLI: The First Romanian Natural Language Inference Corpus (2024.acl-long)

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Challenge: Natural language inference (NLI) is an actively studied topic serving as a proxy for natural language understanding.
Approach: They propose to use a Romanian NLI corpus to analyze sentence pairs . they use multiple machine learning methods to establish competitive baselines .
Outcome: The proposed model improves on the best model by employing a new curriculum learning strategy based on data cartography.
Distilling the Knowledge of Romanian BERTs Using Multiple Teachers (2022.lrec-1)

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Challenge: Existing approaches to train pre-trained language models focus on the English language, thus widening the gap when considering low-resource languages.
Approach: They propose three versions of distilled BERT models for the Romanian language . they argue that the models offer performance comparable to their teachers .
Outcome: The proposed models perform comparable to their teachers, while being twice as fast on a GPU and 35% smaller.
SaRoCo: Detecting Satire in a Novel Romanian Corpus of News Articles (2021.acl-short)

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Challenge: a corpus for satire detection in Romanian news is based on satirical reporting . the goal is to ridicule public figures, politics or contemporary events .
Approach: They propose a corpus for satire detection in Romanian news . they gather 55,608 public news articles from multiple real and satirical sources .
Outcome: The proposed corpus is one of the largest corpora for satire detection regardless of language . it is the only one for the Romanian language, and the results show that it is low on the machine level compared to human level .
RoLargeSum: A Large Dialect-Aware Romanian News Dataset for Summary, Headline, and Keyword Generation (2025.coling-main)

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Challenge: Using supervised automatic summarization requires sufficient corpora that include pairs of documents and their summaries.
Approach: They propose a large-scale summarization dataset for the Romanian language that is crawled from publicly available news websites.
Outcome: The proposed system performs well in abstractive summarization, which involves generating new sentences that capture the essence of the original text rather than extracting and rephrasing existing sentences.
BioRo: The Biomedical Corpus for the Romanian Language (L18-1)

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Challenge: Biomedical text mining uses linguistic resources available in English, but for other languages such as Romanian, the access to language resources is not straight-forward.
Approach: They present a biomedical corpus of the Romanian language, which is a valuable linguistic asset for biomedically text mining.
Outcome: The proposed corpus will be made publicly available to the biomedical text mining community . the corpus is a reference corpus for the Romanian language .
A Bird’s-eye View of Language Processing Projects at the Romanian Academy (L18-1)

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Challenge: a recent article outlines five projects that address contemporary Romanian language . the authors argue that a constant accumulation of human expertise is needed to develop complex projects.
Approach: a new article gives a general overview of five AI language-related projects at the Romanian Academy . they focus on the creation of a contemporary Romanian language text and speech corpus and language related applications .
Outcome: a new article gives an overview of five AI language-related projects at the Romanian Academy . the projects address contemporary Romanian language, as well as language related applications .
Introducing RONEC - the Romanian Named Entity Corpus (2020.lrec-1)

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Challenge: Named Entity Corpus is a free, open-source resource that contains annotated named entities in copy-right free text.
Approach: They present RONEC - the Named Entity Corpus for the Romanian language . it contains over 26000 entities in 5000 annotated sentences belonging to 16 classes .
Outcome: The free, open-source resource contains over 26000 entities in 5000 annotated sentences, belonging to 16 distinct classes.
A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News Articles (2023.findings-emnlp)

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Challenge: Clickbait detection is a task that aims to automatically detect misleading news titles . despite the importance of the task, there is no publicly available clickbait corpus for Romanian .
Approach: They propose a Romanian Clickbait Corpus that automatically detects misleading news titles . they propose four machine learning methods to establish competitive baselines .
Outcome: The proposed model can learn to encode news titles and contents into a deep metric space . the proposed model is available for download on github.com/dariabroscoteanu/RoCliCo.
GRAF: Graph Retrieval Augmented by Facts for Romanian Legal Multi-Choice Question Answering (2025.findings-acl)

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Challenge: Question answering systems have been used for various domains and languages.
Approach: They propose a novel approach for question answering (QA) that combines a dataset of Romanian legal questions with a CROL corpus of laws.
Outcome: The proposed approach achieves competitive results with generally accepted state-of-the-art methods and even exceeds them in most settings.
RSC: A Romanian Read Speech Corpus for Automatic Speech Recognition (2020.lrec-1)

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Challenge: Romanian language is under-resourced due to the lack of acoustic and linguistic resources.
Approach: They propose to use a Romanian speech corpus to train automatic speech recognition algorithms based on the spoken hotword detection mechanism.
Outcome: The read speech corpus is a speech recognition system that can perform automatic speech recognition and speech synthesis using state-of-the-art speech recognition toolkit.
Towards Building the LEMI Readability Platform for Children’s Literature in the Romanian Language (2024.lrec-main)

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Challenge: Currently, no existing platform integrates a research-based readability formula for the Romanian language, making this tool unique.
Approach: They propose a new readability tool for children’s literature in the Romanian language that uses a self-compiled corpus and a text analysis interface to generate automatic readability reports for uploaded short texts.
Outcome: The proposed readability tool is specifically targeted at primary school students aged 7-11 . it extracts, tests, and calibrates a readability formula for Romanian using the children’s literature corpus and the platform functionalities.

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