mlsanityData to 7 Oct 2026

Multilingual State Space Models for Structured Question Answering in Indic Languages

arXiv 2502.01673 ↗First posted 1 Feb 2025cs.CL cs.AIcited by 3

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Abstract (arXiv)

The diversity and complexity of Indic languages present unique challenges for natural language processing (NLP) tasks, particularly in the domain of question answering (QA).To address these challenges, this paper explores the application of State Space Models (SSMs),to build efficient and contextually aware QA systems tailored for Indic languages. SSMs are particularly suited for this task due to their ability to model long-term and short-term dependencies in sequential data, making them well-equipped to handle the rich morphology, complex syntax, and contextual intricacies characteristic of Indian languages. We evaluated multiple SSM architectures across diverse datasets representing various Indic languages and conducted a comparative analysis of their performance. Our results demonstrate that these models effectively capture linguistic subtleties, leading to significant improvements in question interpretation, context alignment, and answer generation. This work represents the first application of SSMs to question answering tasks in Indic languages, establishing a foundational benchmark for future research in this domain. We propose enhancements to existing SSM frameworks, optimizing their applicability to low-resource settings and multilingual scenarios prevalent in Indic languages.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 28 of its 46 references that are in the map. First posted on arXiv 1 Feb 2025.

Builds on

28 of 46 references.

References · 28

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16 more
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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State-Space Architectures from S4 to Mambacited by 9
  2. 2025FUSE : A Ridge and Random Forest-Based Metric for Evaluating MT in Indigenous Languagescited by 0
  3. 2025Tourism Question Answer System in Indian Language using Domain-Adapted Foundation Modelscited by 0