4 citations · 6 across the 5 of their papers we have counts for
6 papers
Contextual Augmentation for Entity Linking using Large Language Models
Daniel Vollmers, Hamada M. Zahera, Diego Moussallem +1
Entity Linking involves detecting and linking entity mentions in natural language texts to a knowledge graph. Traditional methods use a two-step process with separate models for en…
LOLA -- An Open-Source Massively Multilingual Large Language Model
Nikit Srivastava, Denis Kuchelev, Tatiana Moteu Ngoli +5
This paper presents LOLA, a massively multilingual large language model trained on more than 160 languages using a sparse Mixture-of-Experts Transformer architecture. Our architect…
MST5 -- Multilingual Question Answering over Knowledge Graphs
Nikit Srivastava, Mengshi Ma, Daniel Vollmers +3
Knowledge Graph Question Answering (KGQA) simplifies querying vast amounts of knowledge stored in a graph-based model using natural language. However, the research has largely conc…
Universal Knowledge Graph Embeddings
N'Dah Jean Kouagou, Caglar Demir, Hamada M. Zahera +4
A variety of knowledge graph embedding approaches have been developed. Most of them obtain embeddings by learning the structure of the knowledge graph within a link prediction sett…
I-AID: Identifying Actionable Information from Disaster-related Tweets
Hamada M. Zahera, Rricha Jalota, Mohamed A. Sherif +1
Social media plays a significant role in disaster management by providing valuable data about affected people, donations and help requests. Recent studies highlight the need to fil…
Semantic-based End-to-End Learning for Typhoon Intensity Prediction
Hamada M. Zahera, Mohamed Ahmed Sherif, Axel Ngonga
Disaster prediction is one of the most critical tasks towards disaster surveillance and preparedness. Existing technologies employ different machine learning approaches to predict…