6 papers
Fanar-Sadiq: A Multi-Agent Architecture for Grounded Islamic QA
Ummar Abbas, Mourad Ouzzani, Mohamed Y. Eltabakh +7
Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especially consequential in Islamic sett…
Fanar 2.0: Arabic Generative AI Stack
FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad +34
We present Fanar 2.0, the second generation of Qatar's Arabic-centric Generative AI platform. Sovereignty is a first-class design principle: every component, from data pipelines to…
OMNIA: Closing the Loop by Leveraging LLMs for Knowledge Graph Completion
Frédéric Ieng, Soror Sahri, Mourad Ouzzani +5
Knowledge Graphs (KGs) are widely used to represent structured knowledge, yet their automatic construction, especially with Large Language Models (LLMs), often results in incomplet…
HCT-QA: A Benchmark for Question Answering on Human-Centric Tables
Mohammad S. Ahmad, Zan A. Naeem, Michaël Aupetit +6
Tabular data embedded in PDF files, web pages, and other types of documents is prevalent in various domains. These tables, which we call human-centric tables (HCTs for short), are…
Fanar: An Arabic-Centric Multimodal Generative AI Platform
Fanar Team, Ummar Abbas, Mohammad Shahmeer Ahmad +39
We present Fanar, a platform for Arabic-centric multimodal generative AI systems, that supports language, speech and image generation tasks. At the heart of Fanar are Fanar Star an…
RetClean: Retrieval-Based Data Cleaning Using Foundation Models and Data Lakes
Zan Ahmad Naeem, Mohammad Shahmeer Ahmad, Mohamed Eltabakh +2
Can foundation models (such as ChatGPT) clean your data? In this proposal, we demonstrate that indeed ChatGPT can assist in data cleaning by suggesting corrections for specific cel…