An Exploration of Knowledge Editing for Arabic

• URL: http://arxiv.org/abs/2507.09629v1
• Date: Sun, 13 Jul 2025 13:49:52 GMT
• Title: An Exploration of Knowledge Editing for Arabic
• Authors: Basel Mousi, Nadir Durrani, Fahim Dalvi,
• Abstract summary: We evaluate four methods on Arabic translations of the ZsRE and Counterfact benchmarks.<n>Experiments on Llama-2-7B-chat show that parameter-based methods struggle with cross-lingual generalization.<n>We extend Learning-To-Edit (LTE) to a multilingual setting and show that joint Arabic-English training improves both editability and transfer.
• Score: 16.700978644147572
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: While Knowledge Editing (KE) has been widely explored in English, its behavior in morphologically rich languages like Arabic remains underexamined. In this work, we present the first study of Arabic KE. We evaluate four methods (ROME, MEMIT, ICE, and LTE) on Arabic translations of the ZsRE and Counterfact benchmarks, analyzing both multilingual and cross-lingual settings. Our experiments on Llama-2-7B-chat show show that parameter-based methods struggle with cross-lingual generalization, while instruction-tuned methods perform more robustly. We extend Learning-To-Edit (LTE) to a multilingual setting and show that joint Arabic-English training improves both editability and transfer. We release Arabic KE benchmarks and multilingual training for LTE data to support future research.

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