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Rosetta system fine-tunes NileChat-3B for Arabic dialogue translation

By PulseAugur Editorial · [1 sources] ·

Researchers developed the Rosetta system for dialectal Arabic dialogue translation, fine-tuning the NileChat-3B model with LoRA adapters. The system was evaluated on the AlexandriaX shared task, achieving 4th place in the constrained track and 5th in the unconstrained track. Experiments indicated that while external pretraining aided some dialects, it also led to negative transfer, slightly hindering overall performance. AI

IMPACT This research contributes to improved dialectal Arabic translation models, potentially enhancing cross-cultural communication tools.

RANK_REASON The cluster contains an academic paper detailing a new system and its evaluation on a shared task. [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 →

Rosetta system fine-tunes NileChat-3B for Arabic dialogue translation

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15 / 100
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The cluster contains an academic paper detailing a new system and its evaluation on a shared task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Nada Esmaeil, Fathima Rena, Sibi Subhash, Osama Elgendy, Mina Naguib, Salma Omar, Muhammad Arif ·

    Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

    arXiv:2609.10395v1 Announce Type: new Abstract: This paper describes the Rosetta system for Subtask 1 (Context-Aware English-to-Dialectal Arabic Dialogue Translation) of the AlexandriaX shared task, participating in both constrained and unconstrained tracks. The approach fine-tun…

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