A new 27k-sentence Arabic-Russian parallel corpus supports fine-tuned LLM translation benchmarks that improve BLEU by 4.36 and COMET by 0.051 over zero-shot baselines for scientific content.
In: Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script, pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Bridging Scientific Heritage: An Arabic--Russian Parallel Corpus and LLM Benchmark for Sustainable Knowledge Transfer
A new 27k-sentence Arabic-Russian parallel corpus supports fine-tuned LLM translation benchmarks that improve BLEU by 4.36 and COMET by 0.051 over zero-shot baselines for scientific content.