Papers by Anis Charfi

2 papers
Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identification (L18-1)

Copied to clipboard

Challenge: Existing corpus of Arabic textual data is limited to English or other European languages.
Approach: They present a large-scale and multi-dialectal corpus of Tweets from 11 regions and 16 countries in the arab world representing the major Arabic dialectal varieties.
Outcome: The provided corpus will enrich the limited set of available language resources for Arabic and be invaluable enabler for developing author profiling tools and NLP tools for Arabic.
MARASTA: A Multi-dialectal Arabic Cross-domain Stance Corpus (2024.lrec-main)

Copied to clipboard

Challenge: Approximately half of the sentences are in Modern Standard Arabic (MSA) for each region, and the other half is in the region’s respective dialect.
Approach: They propose a cross-domain and multi-dialectal stance corpus for Arabic that includes four regions in the Arab World and covers the main Arabic dialect groups.
Outcome: The proposed corpus outperforms the state-of-the-art dataset in stance detection and dialect and dialect classes.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations