Papers by Andrei-Marius Avram
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. |
MoRoVoc: A Large Dataset for Geographical Variation Identification of the Spoken Romanian Language (2025.findings-emnlp)
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Andrei-Marius Avram, Bănescu Ema-Ioana, Anda-Teodora Robea, Dumitru-Clementin Cercel, Mihaela-Claudia Cercel
| Challenge: | MoRoVoc is the largest dataset for analyzing the regional variation of spoken Romanian . it has more than 93 hours of audio and 88,192 audio samples . |
| Approach: | They propose a multi-target adversarial training framework that incorporates demographic attributes as adversarials for speech models. |
| Outcome: | The proposed model achieves 78.21% accuracy for variation identification of spoken Romanian using gender as an adversarial target. |
RoQLlama: A Lightweight Romanian Adapted Language Model (2024.findings-emnlp)
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| Challenge: | Currently, open-source large language models are limited to tasks involving the English language. |
| Approach: | They propose to use QLoRA to train a Romanian-adapted LLM with 7 billion parameters and quantized to 4 bits to improve model's performance. |
| Outcome: | The proposed model outperforms the other LLMs on four out of the seven tasks investigated using zero-shot prompting. |
The birth of Romanian BERT (2020.findings-emnlp)
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| Challenge: | Large-scale pretrained language models are available in high-resource languages, in particular English, or as multilingual models that compromise performance on individual languages for coverage. |
| Approach: | They propose to use a Romanian transformer-based language model to pretrained a large text corpus to evaluate the model. |
| Outcome: | The proposed model is open-source and can be used in production. |
Distilling the Knowledge of Romanian BERTs Using Multiple Teachers (2022.lrec-1)
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Andrei-Marius Avram, Darius Catrina, Dumitru-Clementin Cercel, Mihai Dascalu, Traian Rebedea, Vasile Pais, Dan Tufis
| 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. |
RoLargeSum: A Large Dialect-Aware Romanian News Dataset for Summary, Headline, and Keyword Generation (2025.coling-main)
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Andrei-Marius Avram, Mircea Timpuriu, Andreea Iuga, Vlad-Cristian Matei, Iulian-Marius Taiatu, Tudor Găină, Dumitru-Clementin Cercel, Mihaela-Claudia Cercel, Florin Pop
| 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. |