Alcides Alcoba Inciarte

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3ranked-venue papers

0as first author

3since 2021 · last 2025

—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence 3 papers		Language models and text generation · 35% Speech recognition and synthesis · 34% Transfer learning and domain adaptation · 31%
Interdisciplinary, comprehensive, and emerging computing 1 paper		Computational social science and digital humanities · 100%
Databases, data mining, and information retrieval 1 paper		Web and social media mining · 100%

Topics — the 6 heaviest of 9, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Natural language and speech › Language models and text generation › multilingual language models arabic language models	0.7	1	2023	JASMINE: Arabic GPT Models for Few-Shot Learning · EMNLP 2023
Machine learning › Transfer learning and domain adaptation › few-shot learning few-shot adaptation	0.7	1	2023	JASMINE: Arabic GPT Models for Few-Shot Learning · EMNLP 2023
Machine learning › Transfer learning and domain adaptation few-shot learning	0.7	1	2023	JASMINE: Arabic GPT Models for Few-Shot Learning · EMNLP 2023
Natural language and speech › Language models and text generation multilingual language models	0.7	1	2023	JASMINE: Arabic GPT Models for Few-Shot Learning · EMNLP 2023
Natural language and speech › Speech recognition and synthesis › speech analysis language identification	0.6	1	2022	AfroLID: A Neural Language Identification Tool for African Languages · EMNLP 2022
Web and social media mining › social media analysis social media text analysis	0.2	1	2022	AfroLID: A Neural Language Identification Tool for African Languages · EMNLP 2022

Methods — techniques the papers use, named apart from their topics

survey · 1.7language resource analysis · 1.7neural language identification · 1.1multi-domain web data · 1.1few-shot evaluation · 0.7GPT model training · 0.7

Year	Publication	Venue	Position
2025	Voice of a Continent: Mapping Africa's Speech Technology Frontier abstract AbdelRahim A. Elmadany, Sang Yun Kwon, Hawau Olamide Toyin, Alcides Alcoba Inciarte, Hanan Aldarmaki, Muhammad Abdul-Mageed. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025. AbdelRahim A. Elmadany, Sang Yun Kwon, Hawau Olamide Toyin, Alcides Alcoba Inciarte, Hanan Aldarmaki, Muhammad Abdul-Mageed	EMNLP	4
2023	JASMINE: Arabic GPT Models for Few-Shot Learning abstract El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, Alcides Inciarte, Md Tawkat Islam Khondaker. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. 2023. El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim A. Elmadany, Alcides Alcoba Inciarte, Md. Tawkat Islam Khondaker	EMNLP	4
2022	AfroLID: A Neural Language Identification Tool for African Languages abstract Language identification (LID) is a crucial precursor for NLP, especially for mining web data.Problematically, most of the world's 7000+ languages today are not covered by LID technologies.We address this pressing issue for Africa by introducing AfroLID, a neural LID toolkit for 517 African languages and varieties.AfroLID exploits a multi-domain web dataset manually curated from across 14 language families utilizing five orthographic systems.When evaluated on our blind Test set, AfroLID achieves 95.89 F 1 -score.We also compare AfroLID to five existing LID tools that each cover a small number of African languages, finding it to outperform them on most languages.We further show the utility of AfroLID in the wild by testing it on the acutely under-served Twitter domain.Finally, we offer a number of controlled case studies and perform a linguistically-motivated error analysis that allow us to both showcase AfroLID's powerful capabilities and limitations.1 Ife Adebara, AbdelRahim A. Elmadany, Muhammad Abdul-Mageed, Alcides Alcoba Inciarte	EMNLP	4