Mutarjim: Advancing Bidirectional Arabic-English Translation with a
  Small Language Model
We introduce Mutarjim, a compact yet powerful language model for
bidirectional Arabic-English translation. While large-scale LLMs have shown
impressive progress in natural language processing tasks, including machine
translation, smaller models. Leveraging this insight, we developed Mutarjim
based on Kuwain-1.5B , a language model tailored for both Arabic and English.
Despite its modest size, Mutarjim outperforms much larger models on several
established benchmarks, achieved through an optimized two-phase training
approach and a carefully curated, high-quality training corpus.. Experimental
results show that Mutarjim rivals models up to 20 times larger while
significantly reducing computational costs and training requirements. We also
introduce Tarjama-25, a new benchmark designed to overcome limitations in
existing Arabic-English benchmarking datasets, such as domain narrowness, short
sentence lengths, and English-source bias. Tarjama-25 comprises 5,000
expert-reviewed sentence pairs and spans a wide range of domains, offering a
more comprehensive and balanced evaluation framework. Notably, Mutarjim
achieves state-of-the-art performance on the English-to-Arabic task in
Tarjama-25, surpassing even significantly larger and proprietary models like
GPT-4o mini. We publicly release Tarjama-25 to support future research and
advance the evaluation of Arabic-English translation systems.
683577db7733c0f27e945847
Khalil Hennara
extracted_confirmed
2025-05-27T09:23:49.563Z
65276c7911a8a521c91bc10f
https://cdn-avatars.huggingface.co/v1/production/uploads/65276c7911a8a521c91bc10f/39dbuUtqQTJERTJ_WkxSh.jpeg
Khalil Hennara
user
Hennara
683577db7733c0f27e945848
Muhammad Hreden
claimed_verified
2025-05-27T10:03:33.725Z
6496df4b3c64d75523a11973
https://cdn-avatars.huggingface.co/v1/production/uploads/6496df4b3c64d75523a11973/I_Qn5-3Czngle-NsGmabO.jpeg
Muhammad Hreden
user
muhammad0-0hreden
683577db7733c0f27e945849
Mohamed Motaism Hamed
extracted_confirmed
2025-06-11T11:38:21.676Z
63aa7667769a10efc404fbbc
https://cdn-avatars.huggingface.co/v1/production/uploads/63aa7667769a10efc404fbbc/tn8ZxUmTEMS0Gze7_F7JL.jpeg
Mohamed Motasim Hamed
user
Moatasem444
683577db7733c0f27e94584a
Zeina Aldallal
extracted_confirmed
2025-06-15T08:47:29.873Z
65704741e1cfce1764ce652e
/avatars/9189aaf417426af4ebe381ed364a6c0e.svg
Zeina Aldallal
user
ZeinaD
683577db7733c0f27e94584b
Sara Chrouf
extracted_confirmed
2025-05-28T13:47:56.996Z
650b64fb443b2a59d4d432e3
/avatars/12f284e007e8b5cddeadf4491a0a1fe8.svg
Sara Chrouf
user
SaraChrouf
683577db7733c0f27e94584c
Safwan AlModhayan
Mutarjim: Advancing Bidirectional Arabic-English Translation with a
  Small Language Model
We introduce Mutarjim, a compact yet powerful language model for
bidirectional Arabic-English translation. While large-scale LLMs have shown
impressive progress in natural language processing tasks, including machine
translation, smaller models. Leveraging this insight, we developed Mutarjim
based on Kuwain-1.5B , a language model tailored for both Arabic and English.
Despite its modest size, Mutarjim outperforms much larger models on several
established benchmarks, achieved through an optimized two-phase training
approach and a carefully curated, high-quality training corpus.. Experimental
results show that Mutarjim rivals models up to 20 times larger while
significantly reducing computational costs and training requirements. We also
introduce Tarjama-25, a new benchmark designed to overcome limitations in
existing Arabic-English benchmarking datasets, such as domain narrowness, short
sentence lengths, and English-source bias. Tarjama-25 comprises 5,000
expert-reviewed sentence pairs and spans a wide range of domains, offering a
more comprehensive and balanced evaluation framework. Notably, Mutarjim
achieves state-of-the-art performance on the English-to-Arabic task in
Tarjama-25, surpassing even significantly larger and proprietary models like
GPT-4o mini. We publicly release Tarjama-25 to support future research and
advance the evaluation of Arabic-English translation systems.
Mutarjim is a compact Arabic-English translation model that outperforms larger models on established benchmarks and achieves state-of-the-art performance on a new comprehensive Tarjama-25 benchmark.
language model bidirectional Arabic-English translation LLMs Kuwain-1.5B two-phase training high-quality training corpus Tarjama-25 domain narrowness English-source bias GPT-4