Author

Christophe Khalil

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#artificial intelligence Preprint Oct 2026

The Instruction Tax on Factual Recall: Base Models Can Beat Their Instruction-Tuned Counterparts

It is shown that the prompting methodology is as important as the model architecture: while the instruction-tuned model version achieves 0.5681 with its chat interface, the base model achieves 0.6836 when prompted using text completion, which decreases factual recall.

Christophe Khalil, Aya Mourad · 0 citations

#natural language process... Preprint Sep 2026

ARAFA: An LLM-Generated Arabic Fact-Checking Dataset

Arafa is introduced, a new large-scale dataset for fact-checking in Modern Standard Arabic, constructed through an automated framework leveraging large language models (LLMs) and presented a scalable approach for developing similar resources for other low-resource languages.

Christophe Khalil, Shady Elbassuoni, Rida Assaf · 0 citations