activity
20202024
most citedA Review on Language Models as Knowledge Bases

63 citations · 80 across the 7 of their papers we have counts for

collaborators

6 papers

cs.CL202210 cited

Meta AI at Arabic Hate Speech 2022: MultiTask Learning with Self-Correction for Hate Speech Classification

Badr AlKhamissi, Mona Diab

In this paper, we tackle the Arabic Fine-Grained Hate Speech Detection shared task and demonstrate significant improvements over reported baselines for its three subtasks. The task…

cs.CL202263 cited

A Review on Language Models as Knowledge Bases

Badr AlKhamissi, Millicent Li, Asli Celikyilmaz +2

Recently, there has been a surge of interest in the NLP community on the use of pretrained Language Models (LMs) as Knowledge Bases (KBs). Researchers have shown that LMs trained o…

cs.NE20212 cited

Deep Spiking Neural Networks with Resonate-and-Fire Neurons

Badr AlKhamissi, Muhammad ElNokrashy, David Bernal-Casas

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.…

cs.LG2021

The Emergence of Abstract and Episodic Neurons in Episodic Meta-RL

Badr AlKhamissi, Muhammad ElNokrashy, Michael Spranger

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)…

cs.CL2021

Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Task

Badr AlKhamissi, Mohamed Gabr, Muhammad ElNokrashy +1

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 subtas…

cs.CL20205 cited

Deep Diacritization: Efficient Hierarchical Recurrence for Improved Arabic Diacritization

Badr AlKhamissi, Muhammad N. ElNokrashy, Mohamed Gabr

We propose a novel architecture for labelling character sequences that achieves state-of-the-art results on the Tashkeela Arabic diacritization benchmark. The core is a two-level r…