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NileChat-3B fine-tuned for dialectal Arabic translation in AlexandriaX-2026 task

By PulseAugur Editorial · [1 sources] ·

A research paper details the submission from team Alkhder for the AlexandriaX-2026 shared task, focusing on English-to-Dialectal Arabic dialogue translation. The team fine-tuned the NileChat-3B model using QLoRA on a specific dialogue corpus, conditioning translations on various contextual factors like target dialect, domain, and participant roles. This approach achieved competitive scores on the test set, with a country-macro-averaged spBLEU of 20.36 and chrF++ of 36.64. AI

IMPACT Demonstrates context-aware translation capabilities for low-resource Arabic dialects, potentially improving cross-cultural communication tools.

RANK_REASON The cluster describes a research paper detailing a system's submission to a shared task, including model fine-tuning and evaluation metrics. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NileChat-3B fine-tuned for dialectal Arabic translation in AlexandriaX-2026 task

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The cluster describes a research paper detailing a system's submission to a shared task, including model fine-tuning and evaluation metrics. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Hasan Alkhder, Maher Pasa, Maria Hanini, Amro Najjar, Ahmet Zengin ·

    alkhder at AlexandriaX-2026: Context-Aware English-to-Dialectal Arabic Dialogue Translation with QLoRA-Fine-Tuned NileChat-3B

    arXiv:2610.22525v1 Announce Type: new Abstract: This paper describes team Alkhder's submission to Subtask 1 of the AlexandriaX-2026 shared task, which asks systems to translate English dialogue turns into thirteen Arabic dialects. We fine-tune NileChat-3B-Base with QLoRA on the A…

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