Zobrazeno 1 - 10
of 297
pro vyhledávání: '"AVRAM, ANDREI A."'
This paper presents the design and evolution of the RELATE platform. It provides a high-performance environment for natural language processing activities, specially constructed for Romanian language. Initially developed for text processing, it has b
Externí odkaz:
http://arxiv.org/abs/2410.21778
Autor:
Dima, George-Andrei, Avram, Andrei-Marius, Crăciun, Cristian-George, Cercel, Dumitru-Clementin
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 Romani
Externí odkaz:
http://arxiv.org/abs/2410.04269
Autor:
Avram, Andrei-Marius, Iuga, Andreea, Manolache, George-Vlad, Matei, Vlad-Cristian, Micliuş, Răzvan-Gabriel, Muntean, Vlad-Andrei, Sorlescu, Manuel-Petru, Şerban, Dragoş-Andrei, Urse, Adrian-Dinu, Păiş, Vasile, Cercel, Dumitru-Clementin
This work introduces HistNERo, the first Romanian corpus for Named Entity Recognition (NER) in historical newspapers. The dataset contains 323k tokens of text, covering more than half of the 19th century (i.e., 1817) until the late part of the 20th c
Externí odkaz:
http://arxiv.org/abs/2405.00155
Autor:
Mănescu, Emilian-Claudiu, Smădu, Răzvan-Alexandru, Avram, Andrei-Marius, Cercel, Dumitru-Clementin, Pop, Florin
Lip reading or visual speech recognition has gained significant attention in recent years, particularly because of hardware development and innovations in computer vision. While considerable progress has been obtained, most models have only been test
Externí odkaz:
http://arxiv.org/abs/2310.04858
Autor:
Avram, Andrei-Marius, Smădu, Răzvan-Alexandru, Păiş, Vasile, Cercel, Dumitru-Clementin, Ion, Radu, Tufiş, Dan
With the rise of bidirectional encoder representations from Transformer models in natural language processing, the speech community has adopted some of their development methodologies. Therefore, the Wav2Vec models were introduced to reduce the data
Externí odkaz:
http://arxiv.org/abs/2306.17792
Autor:
Avram, Andrei-Marius, Mititelu, Verginica Barbu, Păiş, Vasile, Cercel, Dumitru-Clementin, Trăuşan-Matu, Ştefan
Correctly identifying multiword expressions (MWEs) is an important task for most natural language processing systems since their misidentification can result in ambiguity and misunderstanding of the underlying text. In this work, we evaluate the perf
Externí odkaz:
http://arxiv.org/abs/2306.10419
Autor:
Echim, Sebastian-Vasile, Smădu, Răzvan-Alexandru, Avram, Andrei-Marius, Cercel, Dumitru-Clementin, Pop, Florin
Satire detection and sentiment analysis are intensively explored natural language processing (NLP) tasks that study the identification of the satirical tone from texts and extracting sentiments in relationship with their targets. In languages with fe
Externí odkaz:
http://arxiv.org/abs/2306.07845
Developing natural language processing (NLP) systems for social media analysis remains an important topic in artificial intelligence research. This article introduces RoBERTweet, the first Transformer architecture trained on Romanian tweets. Our RoBE
Externí odkaz:
http://arxiv.org/abs/2306.06598
Multiword expressions are a key ingredient for developing large-scale and linguistically sound natural language processing technology. This paper describes our improvements in automatically identifying Romanian multiword expressions on the corpus rel
Externí odkaz:
http://arxiv.org/abs/2304.11350
Autor:
Smădu, Răzvan-Alexandru, Zaharia, George-Eduard, Avram, Andrei-Marius, Cercel, Dumitru-Clementin, Dascalu, Mihai, Pop, Florin
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
Externí odkaz:
http://arxiv.org/abs/2301.06902