Papers by Mahbub E Sobhani
MathMist: A Parallel Multilingual Benchmark Dataset for Mathematical Problem Solving and Reasoning (2026.findings-eacl)
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Mahbub E Sobhani, Md. Faiyaz Abdullah Sayeedi, Tasnim Mohiuddin, Md Mofijul Islam, Swakkhar Shatabda
| Challenge: | Existing benchmarks primarily focus on English or a narrow subset of high-resource languages, leaving significant gaps in assessing multilingual and cross-lingual mathematical reasoning. |
| Approach: | They propose a parallel multilingual benchmark for mathematical problem solving and reasoning that encompasses 2,890 parallel Bangla-English gold standard artifacts. |
| Outcome: | The proposed model encompasses 2,890 parallel Bangla-English gold standard artifacts, totaling 30K aligned question–answer pairs across thirteen languages, representing high-, medium-, and low-resource linguistic settings. |
Do Multi-Agents Solve Better Than Single? Evaluating Agentic Frameworks for Diagram-Grounded Geometry Problem Solving and Reasoning (2026.eacl-srw)
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Mahbub E Sobhani, Md. Faiyaz Abdullah Sayeedi, Mohammad Nehad Alam, Proma Hossain Progga, Swakkhar Shatabda
| Challenge: | Diagram-grounded geometry problem solving is critical for multimodal large language models, but the benefits of multi-agent design over single-aggent remain unclear. |
| Approach: | They compare diagram-grounded geometry problem solving to four visual math benchmarks . they found that multi-agent pipelines provide clear benefits for open-source models . |
| Outcome: | Theorem-based solvers and architectural refinements improve performance on four visual math benchmarks. |