Zobrazeno 1 - 10
of 19
pro vyhledávání: '"ElNokrashy, Muhammad"'
The intricate relationship between language and culture has long been a subject of exploration within the realm of linguistic anthropology. Large Language Models (LLMs), promoted as repositories of collective human knowledge, raise a pivotal question
Externí odkaz:
http://arxiv.org/abs/2402.13231
Autor:
ElNokrashy, Muhammad, AlKhamissi, Badr
Diacritization plays a pivotal role in improving readability and disambiguating the meaning of Arabic texts. Efforts have so far focused on marking every eligible character (Full Diacritization). Comparatively overlooked, Partial Diacritzation (PD) i
Externí odkaz:
http://arxiv.org/abs/2401.08919
A Reverse Dictionary is a tool enabling users to discover a word based on its provided definition, meaning, or description. Such a technique proves valuable in various scenarios, aiding language learners who possess a description of a word without it
Externí odkaz:
http://arxiv.org/abs/2310.15823
Autor:
Alhafni, Bashar, Habash, Nizar, Bouamor, Houda, Obeid, Ossama, Alrowili, Sultan, Alzeer, Daliyah, Alshanqiti, Khawlah M., ElBakry, Ahmed, ElNokrashy, Muhammad, Gabr, Mohamed, Issam, Abderrahmane, Qaddoumi, Abdelrahim, Vijay-Shanker, K., Zyate, Mahmoud
In this paper, we present the results and findings of the Shared Task on Gender Rewriting, which was organized as part of the Seventh Arabic Natural Language Processing Workshop. The task of gender rewriting refers to generating alternatives of a giv
Externí odkaz:
http://arxiv.org/abs/2210.12410
Language Models pretrained on large textual data have been shown to encode different types of knowledge simultaneously. Traditionally, only the features from the last layer are used when adapting to new tasks or data. We put forward that, when using
Externí odkaz:
http://arxiv.org/abs/2209.15168
This paper proposes a simple yet effective method to improve direct (X-to-Y) translation for both cases: zero-shot and when direct data is available. We modify the input tokens at both the encoder and decoder to include signals for the source and tar
Externí odkaz:
http://arxiv.org/abs/2208.05852
In this work, we explore a new Spiking Neural Network (SNN) formulation with Resonate-and-Fire (RAF) neurons (Izhikevich, 2001) trained with gradient descent via back-propagation. The RAF-SNN, while more biologically plausible, achieves performance c
Externí odkaz:
http://arxiv.org/abs/2109.08234
In this work, we analyze the reinstatement mechanism introduced by Ritter et al. (2018) to reveal two classes of neurons that emerge in the agent's working memory (an epLSTM cell) when trained using episodic meta-RL on an episodic variant of the Harl
Externí odkaz:
http://arxiv.org/abs/2104.02959
Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Task
In this paper, we tackle the Nuanced Arabic Dialect Identification (NADI) shared task (Abdul-Mageed et al., 2021) and demonstrate state-of-the-art results on all of its four subtasks. Tasks are to identify the geographic origin of short Dialectal (DA
Externí odkaz:
http://arxiv.org/abs/2103.01065
Autor:
ElNokrashy, Muhammad N., Hendy, Amr, Abdelghaffar, Mohamed, Afify, Mohamed, Tawfik, Ahmed, Awadalla, Hany Hassan
This paper describes our submission to the WMT20 sentence filtering task. We combine scores from (1) a custom LASER built for each source language, (2) a classifier built to distinguish positive and negative pairs by semantic alignment, and (3) the o
Externí odkaz:
http://arxiv.org/abs/2011.07933