TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla

Nishat Raihan; Antonios Anastasopoulos; Marcos Zampieri

doi:10.63317/5nampb63np3m

TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla

Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri

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Abstract

Despite being the 5th most spoken language, Bangla remains underrepresented in Large Language Models (LLMs), particularly for code generation. This primarily stems from the scarcity of high-quality data to pre-train and/or finetune such models. Hence, we introduce the first dedicated family of Code LLMs for Bangla (1B & 9B). We offer three major contributions: (1) a comprehensive Bangla code instruction datasets for programming domain adaptation; (2) MBPP-Bangla, an evaluation benchmark for Bangla code generation; and (3) the TigerCoder-family of Code LLMs, achieving significant ~11-18% performance gains at Pass@1 over existing multilingual and general-purpose Bangla LLMs. Our findings show that curated, high-quality datasets can overcome limitations of smaller models for low-resource languages.

Anthology ID:: 2026.lrec-1.238
Volume:: Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:: LREC
SIG:
Publisher:: ELRA Language Resource Association
Note:
Pages:: 3044–3054
Language:
External URL:: https://lrec.elra.info/lrec2026-main-238
DOI:: 10.63317/5nampb63np3m
Bibkey:
Cite (ACL):: Nishat Raihan, Antonios Anastasopoulos, and Marcos Zampieri. 2026. TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 3044–3054, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):: TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla (Raihan et al., LREC 2026)
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@inproceedings{raihan-etal-2026-tigercoder,
    title = "{T}iger{C}oder: A Novel Suite of {LLM}s for Code Generation in {B}angla",
    author = "Raihan, Nishat  and
      Anastasopoulos, Antonios  and
      Zampieri, Marcos",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://aclanthology.org/2026.lrec-1.238/",
    doi = "10.63317/5nampb63np3m",
    pages = "3044--3054",
    abstract = "Despite being the 5th most spoken language, Bangla remains underrepresented in Large Language Models (LLMs), particularly for code generation. This primarily stems from the scarcity of high-quality data to pre-train and/or finetune such models. Hence, we introduce the first dedicated family of Code LLMs for Bangla (1B {\&} 9B). We offer three major contributions: (1) a comprehensive Bangla code instruction datasets for programming domain adaptation; (2) MBPP-Bangla, an evaluation benchmark for Bangla code generation; and (3) the TigerCoder-family of Code LLMs, achieving significant {\textasciitilde}11-18{\%} performance gains at Pass@1 over existing multilingual and general-purpose Bangla LLMs. Our findings show that curated, high-quality datasets can overcome limitations of smaller models for low-resource languages."
}

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%0 Conference Proceedings
%T TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla
%A Raihan, Nishat
%A Anastasopoulos, Antonios
%A Zampieri, Marcos
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F raihan-etal-2026-tigercoder
%X Despite being the 5th most spoken language, Bangla remains underrepresented in Large Language Models (LLMs), particularly for code generation. This primarily stems from the scarcity of high-quality data to pre-train and/or finetune such models. Hence, we introduce the first dedicated family of Code LLMs for Bangla (1B & 9B). We offer three major contributions: (1) a comprehensive Bangla code instruction datasets for programming domain adaptation; (2) MBPP-Bangla, an evaluation benchmark for Bangla code generation; and (3) the TigerCoder-family of Code LLMs, achieving significant ~11-18% performance gains at Pass@1 over existing multilingual and general-purpose Bangla LLMs. Our findings show that curated, high-quality datasets can overcome limitations of smaller models for low-resource languages.
%R 10.63317/5nampb63np3m
%U https://aclanthology.org/2026.lrec-1.238/
%U https://doi.org/10.63317/5nampb63np3m
%P 3044-3054

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Markdown (Informal)

[TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla](https://aclanthology.org/2026.lrec-1.238/) (Raihan et al., LREC 2026)

TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla (Raihan et al., LREC 2026)

ACL

Nishat Raihan, Antonios Anastasopoulos, and Marcos Zampieri. 2026. TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 3044–3054, Palma de Mallorca, Spain. ELRA Language Resource Association.