RAG System Performance
Arabic Retrieval-Augmented Generation for Alzheimer's Support
ALLaM-RAG is an Arabic Retrieval-Augmented Generation system built for Alzheimer's-related question answering. It combines intelligent retrieval, reranking, and relevant context to improve answer quality, while ALLaM generates context-aware Arabic responses grounded in that retrieved knowledge.
Hybrid retrieval and reranking help identify relevant information.
Arabic language understanding is a core focus.
Responses can be connected to retrieved sources.
A retrieval-augmented pipeline purpose-built for Arabic everyday Alzheimer's related question answering.
Curated Arabic content on Alzheimer’s disease is chunked and indexed for efficient retrieval.
Dense and sparse retrieval jointly surface the most relevant passages for a query.
A reranker reorders candidates so the most contextually relevant passages rise to the top.
ALLaM composes a grounded, context-aware Arabic answer from the retrieved evidence.
Explore how the system responds to Alzheimer's-related questions.
Select a question from the left, or type your own below to begin.
