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Found 21 papers, 8 papers with code
Empathy-driven Arabic Conversational Chatbot
However, the dataset is not large enough to develop very complex encoder-decoder models.
AI Methods for Designing Energy-Efficient Buildings in Urban Environments
Designing energy-efficient buildings is an essential necessity since buildings are responsible for a significant proportion of energy consumption globally.
Empathetic BERT2BERT Conversational Model: Learning Arabic Language Generation with Little Data
The shortcomings of NLG encoder-decoder models are primarily due to the lack of Arabic datasets suitable to train NLG models such as conversational agents.
Empathetic Response Generation
Natural Language Understanding
+3
AraGPT2: Pre-Trained Transformer for Arabic Language Generation
In this paper, we develop the first advanced Arabic language generation model, AraGPT2, trained from scratch on a large Arabic corpus of internet text and news articles.
AraELECTRA: Pre-Training Text Discriminators for Arabic Language Understanding
Advances in English language representation enabled a more sample-efficient pre-training task by Efficiently Learning an Encoder that Classifies Token Replacements Accurately (ELECTRA).
Multi-Task Learning using AraBert for Offensive Language Detection
The shared task on Offensive Language Detection at the OSACT4 has aimed at achieving state of art profane language detection methods for Arabic social media.
AraBERT: Transformer-based Model for Arabic Language Understanding
Recently, with the surge of transformers based models, language-specific BERT based models have proven to be very efficient at language understanding, provided they are pre-trained on a very large corpus.
Ranked #1 on
Sentiment Analysis
on AJGT
SenZi: A Sentiment Analysis Lexicon for the Latinised Arabic (Arabizi)
As such, texts written in Arabizi are often disregarded in sentiment analysis tasks for Arabic.
hULMonA: The Universal Language Model in Arabic
Experiment results show that the developed hULMonA and multi-lingual ULM are able to generalize well to multiple Arabic data sets and achieve new state of the art results in Arabic Sentiment Analysis for some of the tested sets.
Improved Generalization of Arabic Text Classifiers
While transfer learning for text has been very active in the English language, progress in Arabic has been slow, including the use of Domain Adaptation (DA).
Neural Arabic Question Answering
Our system for open domain question answering in Arabic (SOQAL) is based on two components: (1) a document retriever using a hierarchical TF-IDF approach and (2) a neural reading comprehension model using the pre-trained bi-directional transformer BERT.
ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets
Sentiment analysis is a highly subjective and challenging task.
EMA at SemEval-2018 Task 1: Emotion Mining for Arabic
Moreover, several features were evaluated along with different classification and regression techniques.
EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet
We also evaluate EmoWordNet in an emotion recognition task using SemEval 2007 news headlines dataset and we achieve an improvement compared to the use of DepecheMood.
OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based Model
While sentiment analysis in English has achieved significant progress, it remains a challenging task in Arabic given the rich morphology of the language.
A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models
Opinion mining in Arabic is a challenging task given the rich morphology of the language.
CAT: Credibility Analysis of Arabic Content on Twitter
In this paper, we perform an extensive analysis on credibility of Arabic content on Twitter.
Arabic Corpora for Credibility Analysis
We focus on Arabic due to the recent popularity of blogs and microblogs in the Arab World and due to the lack of any such public corpora in Arabic.
