AIConfPaper
← Search

Andrei-Marius Avram

4 accepted papers

2025

MoRoVoc: A Large Dataset for Geographical Variation Identification of the Spoken Romanian Language

Andrei-Marius Avram, B{\u{a}}nescu Ema-Ioana, Anda-Teodora Robea, Dumitru-Clementin Cercel, Mihaela-Claudia Cercel
EMNLP 2025

This paper introduces MoRoVoc, the largest dataset for analyzing the regional variation of spoken Romanian. It has more than 93 hours of audio and 88,192 audio samples, balanced between the Romanian language spoken in Romania and the Republic of Moldova. We further propose a multi-target adversarial

Cited by 0Source ↗PDF ↗Scholar ↗
2025

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

Andrei-Marius Avram, Mircea Timpuriu, Andreea Iuga, Vlad-Cristian Matei, Iulian-Marius Taiatu, Tudor Găină +3
COLING 2025main

Using supervised automatic summarisation methods requires sufficient corpora that include pairs of documents and their summaries. Similarly to many tasks in natural language processing, most of the datasets available for summarization are in English, posing challenges for developing summarization mo…

Cited by 1Source ↗PDF ↗code ↗Scholar ↗
2024

RoQLlama: A Lightweight Romanian Adapted Language Model

George-Andrei Dima, Andrei-Marius Avram, Cristian-George Craciun, Dumitru-Clementin Cercel
EMNLP 2024finding

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 this paper, we aim to advance the performance of Llama2 models on Romanian tasks. We tackle the problem of reduced computi…

Cited by 2Source ↗PDF ↗Scholar ↗
2023

TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)

Răzvan-Alexandru Smădu, George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Mihai Dascalu, Florin Pop
AAAI 2023technical

Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text related to the main topic. In this work, we focus on extracting keyphrases from scientific documents. We introduce TA-DA, a…

Cited by 1Source ↗PDF ↗Scholar ↗