[Submitted on 15 Oct 2026]
Title:alkhder at AlexandriaX-2026: Context-Aware English-to-Dialectal Arabic Dialogue Translation with QLoRA-Fine-Tuned NileChat-3B
View a PDF of the paper titled alkhder at AlexandriaX-2026: Context-Aware English-to-Dialectal Arabic Dialogue Translation with QLoRA-Fine-Tuned NileChat-3B, by Hasan Alkhder and 4 other authors
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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 Alexandria parallel dialogue corpus, training one set of adapter weights for all dialects. Each turn is translated conditioned on the target country and dialect, the domain, the participant roles, the speaker-addressee gender direction, and the preceding dialogue context. At inference, conversations are translated autoregressively and the model is fed its own previous outputs back as context without using any gold target-side test information. Under the constrained track, using only Alexandria data, it trains in about one hour and translates the private test set in under two hours. The system reaches a country-macro-averaged spBLEU of 20.36 and chrF++ of 36.64 on both tracks.
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2610.22525 [cs.CL]
(or arXiv:2610.22525v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2610.22525
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Hasan Alkhder [view email] [v1] Thu, 15 Oct 2026 18:18:39 UTC (33 KB)
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